In this paper, we consider the problem of calculating the node reputation in a Peer-toPeer (P2P) system from fragments of partial knowledge concerned with the trustfulness of nodes which are subjectively given by each node (i.e., evaluator) participating in the system. We are particularly interested in the distributed processing of the calculation of reputation scores while preserving the privacy of evaluators. The basic idea of the proposed method is to extend the EigenTrust reputation management system with the notion of homomorphic cryptosystem. More specifically, it calculates the main eigenvector of a linear system which models the trustfulness of the users (nodes) in the P2P system in a distributed manner, in such a way that: 1) it blocks accesses to the trust value by the nodes to have the secret key used for the decryption, 2) it improves the efficiency of calculation by offloading a part of the task to the participating nodes, and 3) it uses different public keys during the calculation to improve the robustness against the leave of nodes. The performance of the proposed method is evaluated through numerical calculations.
UTILIZING XAI TECHNIQUE TO IMPROVE AUTOENCODER BASED MODEL FOR COMPUTER NETWO...IJCNCJournal
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusion detection, and much more. However, the lack of transparency of ML and DL based models is a major obstacle to their implementation and criticized due to its black-box nature, even with such tremendous results. Explainable Artificial Intelligence (XAI) is a promising area that can improve the trustworthiness of these models by giving explanations and interpreting its output. If the internal working of the ML and DL based models is understandable, then it can further help to improve its performance. The objective of this paper is to show that how XAI can be used to interpret the results of the DL model, the autoencoder in this case. And, based on the interpretation, we improved its performance for computer network anomaly detection. The kernel SHAP method, which is based on the shapley values, is used as a novel feature selection technique. This method is used to identify only those features that are actually causing the anomalous behaviour of the set of attack/anomaly instances. Later, these feature sets are used to train and validate the autoencoderbut on benign data only. Finally, the built SHAP_Model outperformed the other two models proposed based on the feature selection method. This whole experiment is conducted on the subset of the latest CICIDS2017 network dataset. The overall accuracy and AUC of SHAP_Model is 94% and 0.969, respectively.
FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION METHOD TO PROLONG THE NET...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor
network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy consumption
by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck
problem through an efficient message route selection method. The proposed method selects an efficient
messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an
important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the
potential portability of the clustering-based protocol. In addition, the proposed method is updated to find
the optimal path through the genetic algorithm to respond to various environments. We demonstrated the
effectiveness of the proposed method through an experiment in which the proposed method is applied to a
probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
SECURING BGP BY HANDLING DYNAMIC NETWORK BEHAVIOR AND UNBALANCED DATASETSIJCNCJournal
The Border Gateway Protocol (BGP) provides crucial routing information for the Internet infrastructure. A problem with abnormal routing behavior affects the stability and connectivity of the global Internet. The biggest hurdles in detecting BGP attacks are extremely unbalanced data set category distribution and the dynamic nature of the network. This unbalanced class distribution and dynamic nature of the network results in the classifier's inferior performance. In this paper we proposed an efficient approach to properly managing these problems, the proposed approach tackles the unbalanced classification of datasets by turning the problem of binary classification into a problem of multiclass classification. This is achieved by splitting the majority-class samples evenly into multiple segments using Affinity Propagation, where the number of segments is chosen so that the number of samples in any segment closely matches the minority-class samples. Such sections of the dataset together with the minor class are then viewed as different classes and used to train the Extreme Learning Machine (ELM). The RIPE and BCNET datasets are used to evaluate the performance of the proposed technique. When no feature selection is used, the proposed technique improves the F1 score by 1.9% compared to state-of-the-art techniques. With the Fischer feature selection algorithm, the proposed algorithm achieved the highest F1 score of 76.3%, which was a 1.7% improvement over the compared ones. Additionally, the MIQ feature selection technique improves the accuracy by 3.5%. For the BCNET dataset, the proposed technique improves the F1 score by 1.8% for the Fisher feature selection technique. The experimental findings support the substantial improvement in performance from previous approaches by the new technique.
MEKDA: Multi-Level ECC based Key Distribution and Authentication in Internet ...IJCNCJournal
The Internet of Things (IoT) is an extensive system of networks and connected devices with minimal human interaction and swift growth. The constraints of the System and limitations of Devices pose several challenges, including security; hence billions of devices must protect from attacks and compromises. The resource-constrained nature of IoT devices amplifies security challenges. Thus standard data communication and security measures are inefficient in the IoT environment. The ubiquity of IoT devices and their deployment in sensitive applications increase the vulnerability of any security breaches to risk lives. Hence, IoT-related security challenges are of great concern. Authentication is the solution to the vulnerability of a malicious device in the IoT environment. The proposed Multi-level Elliptic Curve Cryptography based Key Distribution and Authentication in IoT enhances the security by Multi-level Authentication when the devices enter or exit the Cluster in an IoT system. The decreased Computation Time and Energy Consumption by generating and distributing Keys using Elliptic Curve Cryptography extends the availability of the IoT devices. The Performance analysis shows the improvement over the Fast Authentication and Data Transfer method.
A COOPERATIVE LOCALIZATION METHOD BASED ON V2I COMMUNICATION AND DISTANCE INF...IJCNCJournal
Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment.
Vehicle positions obtained using V2I communication are more accurate because the known roadside unit
(RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends
more on the number of RSUs; however, the high installation cost limits the use of this approach. It also
depends on nonlinear localization nature. They were neglected in several research papers. In these studies,
the accumulated errors increased with time due to the linearity localization problem. In the present study,
a cooperative localization method based on V2I communication and distance information in vehicular
networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that
the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling
fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem,
but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed
method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the
proposed method has superior accuracy than existing methods, giving a root mean square error of
approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in
fault environments.
A novel algorithm to protect and manage memory locationsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Comparative study on Cache Coherence Protocolsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Ant Colony Optimization for Wireless Sensor Network: A Reviewiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
UTILIZING XAI TECHNIQUE TO IMPROVE AUTOENCODER BASED MODEL FOR COMPUTER NETWO...IJCNCJournal
Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusion detection, and much more. However, the lack of transparency of ML and DL based models is a major obstacle to their implementation and criticized due to its black-box nature, even with such tremendous results. Explainable Artificial Intelligence (XAI) is a promising area that can improve the trustworthiness of these models by giving explanations and interpreting its output. If the internal working of the ML and DL based models is understandable, then it can further help to improve its performance. The objective of this paper is to show that how XAI can be used to interpret the results of the DL model, the autoencoder in this case. And, based on the interpretation, we improved its performance for computer network anomaly detection. The kernel SHAP method, which is based on the shapley values, is used as a novel feature selection technique. This method is used to identify only those features that are actually causing the anomalous behaviour of the set of attack/anomaly instances. Later, these feature sets are used to train and validate the autoencoderbut on benign data only. Finally, the built SHAP_Model outperformed the other two models proposed based on the feature selection method. This whole experiment is conducted on the subset of the latest CICIDS2017 network dataset. The overall accuracy and AUC of SHAP_Model is 94% and 0.969, respectively.
FUZZY LOGIC-BASED EFFICIENT MESSAGE ROUTE SELECTION METHOD TO PROLONG THE NET...IJCNCJournal
Recently, sensor networks have been used in a wide range of applications, and interest in sensor node
performance has increased. A sensor network is composed of tiny nodes with limited resources. The sensor
network communicates between nodes in a configured network through self-organization. An energyefficient security protocol with a hierarchy structure with various advantages has been proposed to
prolong the network lifetime of sensor networks. But due to structural problems in traditional protocols,
nodes located upstream tend to consume relatively high energy compared to other nodes. A network
protocol should be considered to provide minimal security and efficient allocation of energy consumption
by nodes to increase the network lifetime. In this paper, we introduce a solution to solve the bottleneck
problem through an efficient message route selection method. The proposed method selects an efficient
messaging path using GA and fuzzy logic composed of multiple rules. Message route selection plays an
important role in controlling the load balancing of nodes. A principal benefit of the proposed scheme is the
potential portability of the clustering-based protocol. In addition, the proposed method is updated to find
the optimal path through the genetic algorithm to respond to various environments. We demonstrated the
effectiveness of the proposed method through an experiment in which the proposed method is applied to a
probabilistic voting-based filtering scheme that is one of the cluster-based security schemes.
SECURING BGP BY HANDLING DYNAMIC NETWORK BEHAVIOR AND UNBALANCED DATASETSIJCNCJournal
The Border Gateway Protocol (BGP) provides crucial routing information for the Internet infrastructure. A problem with abnormal routing behavior affects the stability and connectivity of the global Internet. The biggest hurdles in detecting BGP attacks are extremely unbalanced data set category distribution and the dynamic nature of the network. This unbalanced class distribution and dynamic nature of the network results in the classifier's inferior performance. In this paper we proposed an efficient approach to properly managing these problems, the proposed approach tackles the unbalanced classification of datasets by turning the problem of binary classification into a problem of multiclass classification. This is achieved by splitting the majority-class samples evenly into multiple segments using Affinity Propagation, where the number of segments is chosen so that the number of samples in any segment closely matches the minority-class samples. Such sections of the dataset together with the minor class are then viewed as different classes and used to train the Extreme Learning Machine (ELM). The RIPE and BCNET datasets are used to evaluate the performance of the proposed technique. When no feature selection is used, the proposed technique improves the F1 score by 1.9% compared to state-of-the-art techniques. With the Fischer feature selection algorithm, the proposed algorithm achieved the highest F1 score of 76.3%, which was a 1.7% improvement over the compared ones. Additionally, the MIQ feature selection technique improves the accuracy by 3.5%. For the BCNET dataset, the proposed technique improves the F1 score by 1.8% for the Fisher feature selection technique. The experimental findings support the substantial improvement in performance from previous approaches by the new technique.
MEKDA: Multi-Level ECC based Key Distribution and Authentication in Internet ...IJCNCJournal
The Internet of Things (IoT) is an extensive system of networks and connected devices with minimal human interaction and swift growth. The constraints of the System and limitations of Devices pose several challenges, including security; hence billions of devices must protect from attacks and compromises. The resource-constrained nature of IoT devices amplifies security challenges. Thus standard data communication and security measures are inefficient in the IoT environment. The ubiquity of IoT devices and their deployment in sensitive applications increase the vulnerability of any security breaches to risk lives. Hence, IoT-related security challenges are of great concern. Authentication is the solution to the vulnerability of a malicious device in the IoT environment. The proposed Multi-level Elliptic Curve Cryptography based Key Distribution and Authentication in IoT enhances the security by Multi-level Authentication when the devices enter or exit the Cluster in an IoT system. The decreased Computation Time and Energy Consumption by generating and distributing Keys using Elliptic Curve Cryptography extends the availability of the IoT devices. The Performance analysis shows the improvement over the Fast Authentication and Data Transfer method.
A COOPERATIVE LOCALIZATION METHOD BASED ON V2I COMMUNICATION AND DISTANCE INF...IJCNCJournal
Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment.
Vehicle positions obtained using V2I communication are more accurate because the known roadside unit
(RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends
more on the number of RSUs; however, the high installation cost limits the use of this approach. It also
depends on nonlinear localization nature. They were neglected in several research papers. In these studies,
the accumulated errors increased with time due to the linearity localization problem. In the present study,
a cooperative localization method based on V2I communication and distance information in vehicular
networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that
the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling
fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem,
but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed
method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the
proposed method has superior accuracy than existing methods, giving a root mean square error of
approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in
fault environments.
A novel algorithm to protect and manage memory locationsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Comparative study on Cache Coherence Protocolsiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Ant Colony Optimization for Wireless Sensor Network: A Reviewiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
STUDY OF DISTANCE MEASUREMENT TECHNIQUES IN CONTEXT TO PREDICTION MODEL OF WE...ijscai
Internet is the boon in modern era as every organization uses it for dissemination of information and ecommerce
related applications. Sometimes people of organization feel delay while accessing internet in
spite of proper bandwidth. Prediction model of web caching and prefetching is an ideal solution of this
delay problem. Prediction model analysing history of internet user from server raw log files and determine
future sequence of web objects and placed all web objects to nearer to the user so access latency could be
reduced to some extent and problem of delay is to be solved. To determine sequence of future web objects,
it is necessary to determine proximity of one web object with other by identifying proper distance metric
technique related to web caching and prefetching. This paper studies different distance metric techniques
and concludes that bio informatics based distance metric techniques are ideal in context to Web Caching
and Web Prefetching
Internet Worm Classification and Detection using Data Mining Techniquesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Image Based Relational Database Watermarking: A Surveyiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Online stream mining approach for clustering network trafficeSAT Journals
Abstract A large number of research have been proposed on intrusion detection system, which leads to the implementation of agent based intelligent IDS (IIDS), Non – intelligent IDS (NIDS), signature based IDS etc. While building such IDS models, learning algorithms from flow of network traffic plays crucial role in accuracy of IDS systems. The proposed work focuses on implementing the novel method to cluster network traffic which eliminates the limitations in existing online clustering algorithms and prove the robustness and accuracy over large stream of network traffic arriving at extremely high rate. We compare the existing algorithm with novel methods to analyse the accuracy and complexity. Keywords— NIDS, Data Stream Mining, Online Clustering, RAH algorithm, Online Efficient Incremental Clustering algorithm
Intrusion detection with Parameterized Methods for Wireless Sensor Networksrahulmonikasharma
Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two Adaboost based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.
Minkowski Distance based Feature Selection Algorithm for Effective Intrusion ...IJMER
Intrusion Detection System (IDS) plays a major role in the provision of effective security to various types of networks. Moreover, Intrusion Detection System for networks need appropriate rule set for classifying network bench mark data into normal or attack patterns. Generally, each dataset is characterized by a large set of features. However, all these features will not be relevant or fully contribute in identifying an attack. Since different attacks need various subsets to provide better detection accuracy. In this paper an improved feature selection algorithm is proposed to identify the most appropriate subset of features for detecting a certain attacks. This proposed method is based on Minkowski distance feature ranking and an improved exhaustive search that selects a better combination of features. This system has been evaluated using the KDD CUP 1999 dataset and also with EMSVM [1] classifier. The experimental results show that the proposed system provides high classification accuracy and low false alarm rate when applied on the reduced feature subsets
New kind of intrusions causes deviation in the normal behaviour of traffic flow in
computer networks every day. This study focused on enhancing the learning capabilities of IDS
to detect the anomalies present in a network traffic flow by comparing the k-means approach of
data mining for intrusion detection and the outlier detection approach. The k-means approach
uses clustering mechanisms to group the traffic flow data into normal and abnormal clusters.
Outlier detection calculates an outlier score (neighbourhood outlier factor (NOF)) for each flow
record, whose value decides whether a traffic flow is normal or abnormal. These two methods
were then compared in terms of various performance metrics and the amount of computer
resources consumed by them. Overall, k-means was more accurate and precise and has better
classification rate than outlier detection in intrusion detection using traffic flows. This will help
systems administrators in their choice of IDS.
SAMPLING BASED APPROACHES TO HANDLE IMBALANCES IN NETWORK TRAFFIC DATASET FOR...cscpconf
Network traffic data is huge, varying and imbalanced because various classes are not equally distributed. Machine learning (ML) algorithms for traffic analysis uses the samples from this
data to recommend the actions to be taken by the network administrators as well as training. Due to imbalances in dataset, it is difficult to train machine learning algorithms for traffic
analysis and these may give biased or false results leading to serious degradation in performance of these algorithms. Various techniques can be applied during sampling to minimize the effect of imbalanced instances. In this paper various sampling techniques have been analysed in order to compare the decrease in variation in imbalances of network traffic
datasets sampled for these algorithms. Various parameters like missing classes in samples probability of sampling of the different instances have been considered for comparison
A Heuristic Approach for Network Data Clusteringidescitation
In this growing world of technology there are lots of security threats received by
each and every area of computer networks. Most of the time the network security threats
produce high false positive and negative ratios, this creates an obstacle for any security
system to work improperly. The overwhelming threats make it challenging to understand
and manage the network data.
To address this problem we present a novel approach which eventually understand the
network data by clustering them without background knowledge of any threats according to
various parameters like source IP, Destination IP etc. And this approach saves
administrator’s time and energy in processing of large amount threats.
SURVEY PAPER ON PRIVACY IN LOCATION BASED SEARCH QUERIES.ijiert bestjournal
Due to tremendous growth in mobile phones,the mark et for Location Based Services is growing fast. Man y mobile phone applications uses location based services suc h as nearest store finder,car navigation system et c. Location � Based Services provides services to mobile device u sers based on the location information as well as d ata profile of the users. Using these services mobile users retrie ve information about nearest POI. This involves loc ation and data profile of the user�s to be misused. In order to pr otect user�s private information many solutions ar e offered but most of them only addressed on snapshot and no supp ort for continuous query and MQMO .Some papers add ressed MQMO but fails to provide privacy. This paper focus es on MQMO and also protect user�s private informat ion using PIR (private information retrieval) .
Anew approach to broadcast in wormhole routed three-dimensional networks is proposed. One of the most
important process in communication and parallel computer is broadcast approach.. The approach of this
case of Broadcasting is to send the message from one source to all destinations in the network which
corresponds to one-to-all communication. Wormhole routing is a fundamental routing mechanism in
modern parallel computers which is characterized with low communication latency. We show how to apply
this approach to 3-D meshes. Wormhole routing is divided the packets into set of FLITS (flow control
digits). The first Flit of the packet (Header Flit) is containing the destination address and all subsets flits
will follow the routing way of the header Flit. In this paper, we consider an efficient algorithm for
broadcasting on an all-port wormhole-routed 3D mesh with arbitrary size. We introduce an efficient
algorithm, Y-Hamiltonian Layers Broadcast(Y-HLB). In this paper the behaviors of this algorithm were
compared to the previous results, our paradigm reduces broadcast latency and is simpler. In this paper our
simulation results show the average of our proposed algorithm over the other algorithms that presented.
Evaluation of network intrusion detection using markov chainIJCI JOURNAL
Day today life internet threat has been increased significantly. There is a need to develop model in order to
maintain security of system. The most effective techniques are Intrusion Detection System (IDS).The
purpose of intrusion system through the security devices detect and deal with it. In this paper, a
mathematical approach is used effectively to predict and detect intrusion in the network. Here we discuss
about two algorithms ‘K-Means + Apriori’, a method which classify normal and abnormal activities in
computer network. In K-Means process, it partitions the training set into K-clusters using Euclidean
distance and introduce an outlier factor, then it build Apriori Algorithm to prune the data by removing
infrequent data in the database. Based on defined state the degree of incoming data is evaluated through
the experiment using sample DARPA2000 dataset, and achieves high detection performance in level of
attack in stages.
A Novel Classification via Clustering Method for Anomaly Based Network Intrus...IDES Editor
Intrusion detection in the internet is an active
area of research. Intruders can be classified into two
types, namely; external intruders who are unauthorized
users of the computers they attack, and internal
intruders, who have permission to access the system but
with some restrictions. The aim of this paper is to present
a methodology to recognize attacks during the normal
activities in a system. A novel classification via sequential
information bottleneck (sIB) clustering algorithm has
been proposed to build an efficient anomaly based
network intrusion detection model. We have compared
our proposed method with other clustering algorithms
like X-Means, Farthest First, Filtered clusters, DBSCAN,
K-Means, and EM (Expectation-Maximization)
clustering in order to find the suitability of our proposed
algorithm. A subset of KDDCup 1999 intrusion detection
benchmark dataset has been used for the experiment.
Results show that the proposed method is efficient in
terms of detection accuracy, low false positive rate in
comparison to the other existing methods.
Intrusion Detection System Using Self Organizing Map AlgorithmsEditor IJCATR
With the rapid expansion of computer usage and computer network the security of the computer system has became very
im
portant. Every day new kind of attacks are being faced by industries. Many methods have been proposed for the development of
intrusion detection system using artificial intelligence technique. In this paper we will have a look at an algorithm based o
n neur
al
networks that are suitable for Intrusion Detection Systems (IDS)
.
The name of this
algorithm is "Self Organizing Maps" (SOM).
So
far, many different methods have been used to build a detector that Wide variety of different ways in the covers. Among the
methods
used to detect attacks in intrusion detection is done, In this paper we investigate the
Self
-
Organizing
Map
method.
PROOF-OF-REPUTATION: AN ALTERNATIVE CONSENSUS MECHANISM FOR BLOCKCHAIN SYSTEMSIJNSA Journal
Blockchains combine other technologies, such as cryptography, networking, and incentive mechanisms, to enable the creation, validation, and recording of transactions between participating nodes. A consensus algorithm is used in a blockchain system to determine the shared state among distributed nodes. An important component underlying any blockchain-based system is its consensus mechanism, which principally determines the performance and security of the overall system. As the nature of peer-topeer(P2P) networks is open and dynamic, the security risk within that environment is greatly increased mostly because nodes can join and leave the network at will. Thus, it is important to have a system that can check against malicious behaviour. In this work, we propose a reputation-based consensus mechanism for blockchain-based systems, Proof-of-Reputation(PoR) where the nodes with the highest reputation values eventually become part of a consensus group that determines the state of the blockchain.
PUBLIC INTEGRIYT AUDITING FOR SHARED DYNAMIC DATA STORAGE UNDER ONTIME GENERA...paperpublications3
Abstract: Nowadays verifying the result of the remote computation plays a crucial role in addressing in issue of trust. The outsourced data collection comes for multiple data sources to diagnose the originator of errors by allotting each data sources a unique secrete key which requires the inner product conformation to be performed under any two parties different keys. The proposed methods outperform AISM technique to minimize the running time. The multi-key setting is given different secrete keys, multiple data sources can be upload their data streams along with their respective verifiable homomorphic tag. The AISM consist of three novel join techniques depending on the ADS availability: (i) Authenticated Indexed Sort Merge Join (AISM), which utilizes a single ADS on the join attribute, (ii) Authenticated Index Merge Join (AIM) that requires an ADS (on the join attribute) for both relations, and (iii) Authenticated Sort Merge Join (ASM), which does not rely on any ADS. The client should allow choosing any portion in the data streams for queries. The communication between the client and server is independent of input size. The inner product evaluation can be performed by any two sources and the result can be verified by using the particular tag.
Keywords: Computation of outsourcing, Data Stream, Multiple Key, Homomorphic encryption.
Title: PUBLIC INTEGRIYT AUDITING FOR SHARED DYNAMIC DATA STORAGE UNDER ONTIME GENERATED MULTIPLE KEYS
Author: C. NISHA MALAR, M. S. BONSHIA BINU
ISSN 2350-1049
International Journal of Recent Research in Interdisciplinary Sciences (IJRRIS)
Paper Publications
IMPROVING HYBRID REPUTATION MODEL THROUGH DYNAMIC REGROUPINGijp2p
Peer-to-Peer (P2P) systems have the ability to bond with millions of clients in business and knowledge
scenario. The mechanism that leads users to distribute files without the need of centralized servers has
achieved wide recognition among internet users. This also permits for a range of applications further than
simple file sharing. he main problem lies in the fact that peers have to customarily intermingle with
mysterious peers in the absence of trusted third parties. Usually the lack of incentives often makes these
strange peers to act as freeriders and thus reduce the system performance. The trustworthiness among
peers is portrayed by applying the knowledge obtained as a result of reputation mechanisms. This paper
endows with a new reputation model in association with a detailed survey of diverse reputation models. The
proposed model suggests a hybrid reputation model through dynamic regrouping..
Advanced Data Protection and Key Organization Framework for Mobile Ad-Hoc Net...AM Publications,India
Key organization and protect routing are two major subjects for Mobile Ad-hoc Networks nonetheless preceding explanations tend to contemplate them distinctly. This indicates to Key organization and protects routing inters dependency cycle problem. In this paper, we recommend a Key organization and protection of routing integrated scheme that speeches Key organization and protection of routing inter dependency cycle problem. By using identity based cryptography this scheme delivers produced including confidentiality, honesty, verification, cleanness, and non-repudiation. Connected to symmetric cryptography and conventional asymmetric cryptography as well as preceding IBC arrangements, this arrangement has developments in many features. We deliver hypothetical resistant of the refuge of the scheme and validate the efficiency of the scheme with applied simulation.
Reputation-Based Consensus for Blockchain Technology in Smart GridIJNSA Journal
Accurate and thorough measurement of all nodes’ trustworthiness should create a safer network environment. We designed a blockchain-based, completely self-operated reputation system, R360, to enhance network security in decentralized network. R360 is a multi-factor measurement on the reputation of all nodes in the network. Specifically, a node’s function, defense capability, quality of service provided, availability, malicious behavior, and resources are evaluated, providing a more accurate picture about a node’s trustworthiness, which in turn should enhance the security of blockchain operations in a non-trust environment. Our design has been implemented on a single-machine, simulated setting, which demonstrates that, comparing to systems with few dimensions, R360’s consensus took less time while at the same time providing better security to the system. Further security analysis shows that our design can defend common security attacks on reputation systems. Such a blockchain-based, self-operated reputation system could be used to manage smat grids for more efficient energy production and delivery.
STUDY OF DISTANCE MEASUREMENT TECHNIQUES IN CONTEXT TO PREDICTION MODEL OF WE...ijscai
Internet is the boon in modern era as every organization uses it for dissemination of information and ecommerce
related applications. Sometimes people of organization feel delay while accessing internet in
spite of proper bandwidth. Prediction model of web caching and prefetching is an ideal solution of this
delay problem. Prediction model analysing history of internet user from server raw log files and determine
future sequence of web objects and placed all web objects to nearer to the user so access latency could be
reduced to some extent and problem of delay is to be solved. To determine sequence of future web objects,
it is necessary to determine proximity of one web object with other by identifying proper distance metric
technique related to web caching and prefetching. This paper studies different distance metric techniques
and concludes that bio informatics based distance metric techniques are ideal in context to Web Caching
and Web Prefetching
Internet Worm Classification and Detection using Data Mining Techniquesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Image Based Relational Database Watermarking: A Surveyiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Online stream mining approach for clustering network trafficeSAT Journals
Abstract A large number of research have been proposed on intrusion detection system, which leads to the implementation of agent based intelligent IDS (IIDS), Non – intelligent IDS (NIDS), signature based IDS etc. While building such IDS models, learning algorithms from flow of network traffic plays crucial role in accuracy of IDS systems. The proposed work focuses on implementing the novel method to cluster network traffic which eliminates the limitations in existing online clustering algorithms and prove the robustness and accuracy over large stream of network traffic arriving at extremely high rate. We compare the existing algorithm with novel methods to analyse the accuracy and complexity. Keywords— NIDS, Data Stream Mining, Online Clustering, RAH algorithm, Online Efficient Incremental Clustering algorithm
Intrusion detection with Parameterized Methods for Wireless Sensor Networksrahulmonikasharma
Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two Adaboost based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.
Minkowski Distance based Feature Selection Algorithm for Effective Intrusion ...IJMER
Intrusion Detection System (IDS) plays a major role in the provision of effective security to various types of networks. Moreover, Intrusion Detection System for networks need appropriate rule set for classifying network bench mark data into normal or attack patterns. Generally, each dataset is characterized by a large set of features. However, all these features will not be relevant or fully contribute in identifying an attack. Since different attacks need various subsets to provide better detection accuracy. In this paper an improved feature selection algorithm is proposed to identify the most appropriate subset of features for detecting a certain attacks. This proposed method is based on Minkowski distance feature ranking and an improved exhaustive search that selects a better combination of features. This system has been evaluated using the KDD CUP 1999 dataset and also with EMSVM [1] classifier. The experimental results show that the proposed system provides high classification accuracy and low false alarm rate when applied on the reduced feature subsets
New kind of intrusions causes deviation in the normal behaviour of traffic flow in
computer networks every day. This study focused on enhancing the learning capabilities of IDS
to detect the anomalies present in a network traffic flow by comparing the k-means approach of
data mining for intrusion detection and the outlier detection approach. The k-means approach
uses clustering mechanisms to group the traffic flow data into normal and abnormal clusters.
Outlier detection calculates an outlier score (neighbourhood outlier factor (NOF)) for each flow
record, whose value decides whether a traffic flow is normal or abnormal. These two methods
were then compared in terms of various performance metrics and the amount of computer
resources consumed by them. Overall, k-means was more accurate and precise and has better
classification rate than outlier detection in intrusion detection using traffic flows. This will help
systems administrators in their choice of IDS.
SAMPLING BASED APPROACHES TO HANDLE IMBALANCES IN NETWORK TRAFFIC DATASET FOR...cscpconf
Network traffic data is huge, varying and imbalanced because various classes are not equally distributed. Machine learning (ML) algorithms for traffic analysis uses the samples from this
data to recommend the actions to be taken by the network administrators as well as training. Due to imbalances in dataset, it is difficult to train machine learning algorithms for traffic
analysis and these may give biased or false results leading to serious degradation in performance of these algorithms. Various techniques can be applied during sampling to minimize the effect of imbalanced instances. In this paper various sampling techniques have been analysed in order to compare the decrease in variation in imbalances of network traffic
datasets sampled for these algorithms. Various parameters like missing classes in samples probability of sampling of the different instances have been considered for comparison
A Heuristic Approach for Network Data Clusteringidescitation
In this growing world of technology there are lots of security threats received by
each and every area of computer networks. Most of the time the network security threats
produce high false positive and negative ratios, this creates an obstacle for any security
system to work improperly. The overwhelming threats make it challenging to understand
and manage the network data.
To address this problem we present a novel approach which eventually understand the
network data by clustering them without background knowledge of any threats according to
various parameters like source IP, Destination IP etc. And this approach saves
administrator’s time and energy in processing of large amount threats.
SURVEY PAPER ON PRIVACY IN LOCATION BASED SEARCH QUERIES.ijiert bestjournal
Due to tremendous growth in mobile phones,the mark et for Location Based Services is growing fast. Man y mobile phone applications uses location based services suc h as nearest store finder,car navigation system et c. Location � Based Services provides services to mobile device u sers based on the location information as well as d ata profile of the users. Using these services mobile users retrie ve information about nearest POI. This involves loc ation and data profile of the user�s to be misused. In order to pr otect user�s private information many solutions ar e offered but most of them only addressed on snapshot and no supp ort for continuous query and MQMO .Some papers add ressed MQMO but fails to provide privacy. This paper focus es on MQMO and also protect user�s private informat ion using PIR (private information retrieval) .
Anew approach to broadcast in wormhole routed three-dimensional networks is proposed. One of the most
important process in communication and parallel computer is broadcast approach.. The approach of this
case of Broadcasting is to send the message from one source to all destinations in the network which
corresponds to one-to-all communication. Wormhole routing is a fundamental routing mechanism in
modern parallel computers which is characterized with low communication latency. We show how to apply
this approach to 3-D meshes. Wormhole routing is divided the packets into set of FLITS (flow control
digits). The first Flit of the packet (Header Flit) is containing the destination address and all subsets flits
will follow the routing way of the header Flit. In this paper, we consider an efficient algorithm for
broadcasting on an all-port wormhole-routed 3D mesh with arbitrary size. We introduce an efficient
algorithm, Y-Hamiltonian Layers Broadcast(Y-HLB). In this paper the behaviors of this algorithm were
compared to the previous results, our paradigm reduces broadcast latency and is simpler. In this paper our
simulation results show the average of our proposed algorithm over the other algorithms that presented.
Evaluation of network intrusion detection using markov chainIJCI JOURNAL
Day today life internet threat has been increased significantly. There is a need to develop model in order to
maintain security of system. The most effective techniques are Intrusion Detection System (IDS).The
purpose of intrusion system through the security devices detect and deal with it. In this paper, a
mathematical approach is used effectively to predict and detect intrusion in the network. Here we discuss
about two algorithms ‘K-Means + Apriori’, a method which classify normal and abnormal activities in
computer network. In K-Means process, it partitions the training set into K-clusters using Euclidean
distance and introduce an outlier factor, then it build Apriori Algorithm to prune the data by removing
infrequent data in the database. Based on defined state the degree of incoming data is evaluated through
the experiment using sample DARPA2000 dataset, and achieves high detection performance in level of
attack in stages.
A Novel Classification via Clustering Method for Anomaly Based Network Intrus...IDES Editor
Intrusion detection in the internet is an active
area of research. Intruders can be classified into two
types, namely; external intruders who are unauthorized
users of the computers they attack, and internal
intruders, who have permission to access the system but
with some restrictions. The aim of this paper is to present
a methodology to recognize attacks during the normal
activities in a system. A novel classification via sequential
information bottleneck (sIB) clustering algorithm has
been proposed to build an efficient anomaly based
network intrusion detection model. We have compared
our proposed method with other clustering algorithms
like X-Means, Farthest First, Filtered clusters, DBSCAN,
K-Means, and EM (Expectation-Maximization)
clustering in order to find the suitability of our proposed
algorithm. A subset of KDDCup 1999 intrusion detection
benchmark dataset has been used for the experiment.
Results show that the proposed method is efficient in
terms of detection accuracy, low false positive rate in
comparison to the other existing methods.
Intrusion Detection System Using Self Organizing Map AlgorithmsEditor IJCATR
With the rapid expansion of computer usage and computer network the security of the computer system has became very
im
portant. Every day new kind of attacks are being faced by industries. Many methods have been proposed for the development of
intrusion detection system using artificial intelligence technique. In this paper we will have a look at an algorithm based o
n neur
al
networks that are suitable for Intrusion Detection Systems (IDS)
.
The name of this
algorithm is "Self Organizing Maps" (SOM).
So
far, many different methods have been used to build a detector that Wide variety of different ways in the covers. Among the
methods
used to detect attacks in intrusion detection is done, In this paper we investigate the
Self
-
Organizing
Map
method.
PROOF-OF-REPUTATION: AN ALTERNATIVE CONSENSUS MECHANISM FOR BLOCKCHAIN SYSTEMSIJNSA Journal
Blockchains combine other technologies, such as cryptography, networking, and incentive mechanisms, to enable the creation, validation, and recording of transactions between participating nodes. A consensus algorithm is used in a blockchain system to determine the shared state among distributed nodes. An important component underlying any blockchain-based system is its consensus mechanism, which principally determines the performance and security of the overall system. As the nature of peer-topeer(P2P) networks is open and dynamic, the security risk within that environment is greatly increased mostly because nodes can join and leave the network at will. Thus, it is important to have a system that can check against malicious behaviour. In this work, we propose a reputation-based consensus mechanism for blockchain-based systems, Proof-of-Reputation(PoR) where the nodes with the highest reputation values eventually become part of a consensus group that determines the state of the blockchain.
PUBLIC INTEGRIYT AUDITING FOR SHARED DYNAMIC DATA STORAGE UNDER ONTIME GENERA...paperpublications3
Abstract: Nowadays verifying the result of the remote computation plays a crucial role in addressing in issue of trust. The outsourced data collection comes for multiple data sources to diagnose the originator of errors by allotting each data sources a unique secrete key which requires the inner product conformation to be performed under any two parties different keys. The proposed methods outperform AISM technique to minimize the running time. The multi-key setting is given different secrete keys, multiple data sources can be upload their data streams along with their respective verifiable homomorphic tag. The AISM consist of three novel join techniques depending on the ADS availability: (i) Authenticated Indexed Sort Merge Join (AISM), which utilizes a single ADS on the join attribute, (ii) Authenticated Index Merge Join (AIM) that requires an ADS (on the join attribute) for both relations, and (iii) Authenticated Sort Merge Join (ASM), which does not rely on any ADS. The client should allow choosing any portion in the data streams for queries. The communication between the client and server is independent of input size. The inner product evaluation can be performed by any two sources and the result can be verified by using the particular tag.
Keywords: Computation of outsourcing, Data Stream, Multiple Key, Homomorphic encryption.
Title: PUBLIC INTEGRIYT AUDITING FOR SHARED DYNAMIC DATA STORAGE UNDER ONTIME GENERATED MULTIPLE KEYS
Author: C. NISHA MALAR, M. S. BONSHIA BINU
ISSN 2350-1049
International Journal of Recent Research in Interdisciplinary Sciences (IJRRIS)
Paper Publications
IMPROVING HYBRID REPUTATION MODEL THROUGH DYNAMIC REGROUPINGijp2p
Peer-to-Peer (P2P) systems have the ability to bond with millions of clients in business and knowledge
scenario. The mechanism that leads users to distribute files without the need of centralized servers has
achieved wide recognition among internet users. This also permits for a range of applications further than
simple file sharing. he main problem lies in the fact that peers have to customarily intermingle with
mysterious peers in the absence of trusted third parties. Usually the lack of incentives often makes these
strange peers to act as freeriders and thus reduce the system performance. The trustworthiness among
peers is portrayed by applying the knowledge obtained as a result of reputation mechanisms. This paper
endows with a new reputation model in association with a detailed survey of diverse reputation models. The
proposed model suggests a hybrid reputation model through dynamic regrouping..
Advanced Data Protection and Key Organization Framework for Mobile Ad-Hoc Net...AM Publications,India
Key organization and protect routing are two major subjects for Mobile Ad-hoc Networks nonetheless preceding explanations tend to contemplate them distinctly. This indicates to Key organization and protects routing inters dependency cycle problem. In this paper, we recommend a Key organization and protection of routing integrated scheme that speeches Key organization and protection of routing inter dependency cycle problem. By using identity based cryptography this scheme delivers produced including confidentiality, honesty, verification, cleanness, and non-repudiation. Connected to symmetric cryptography and conventional asymmetric cryptography as well as preceding IBC arrangements, this arrangement has developments in many features. We deliver hypothetical resistant of the refuge of the scheme and validate the efficiency of the scheme with applied simulation.
Reputation-Based Consensus for Blockchain Technology in Smart GridIJNSA Journal
Accurate and thorough measurement of all nodes’ trustworthiness should create a safer network environment. We designed a blockchain-based, completely self-operated reputation system, R360, to enhance network security in decentralized network. R360 is a multi-factor measurement on the reputation of all nodes in the network. Specifically, a node’s function, defense capability, quality of service provided, availability, malicious behavior, and resources are evaluated, providing a more accurate picture about a node’s trustworthiness, which in turn should enhance the security of blockchain operations in a non-trust environment. Our design has been implemented on a single-machine, simulated setting, which demonstrates that, comparing to systems with few dimensions, R360’s consensus took less time while at the same time providing better security to the system. Further security analysis shows that our design can defend common security attacks on reputation systems. Such a blockchain-based, self-operated reputation system could be used to manage smat grids for more efficient energy production and delivery.
A Framework for Secure Computations with Two Non-Colluding Servers and Multip...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
A MALICIOUS USERS DETECTING MODEL BASED ON FEEDBACK CORRELATIONSIJCNC
The trust and reputation models were introduced to restrain the impacts caused by rational but selfish
peers in P2P streaming systems. However, these models face with two major challenges from dishonest
feedback and strategic altering behaviors. To answer these challenges, we present a global trust model
based on network community, evaluation correlations, and punishment mechanism. We also propose a
two-layered overlay to provide the function of peers’ behaviors collection and malicious detection.
Furthermore, we analysis several security threats in P2P streaming systems, and discuss how to defend
with them by our trust mechanism. The simulation results show that our trust framework can successfully
filter out dishonest feedbacks by using correlation coefficients. It can effectively defend against the
security threats with good load balance as well.
Space-efficient Verifiable Secret Sharing Using Polynomial Interpolationnexgentechnology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Space efficient verifiable secret sharingnexgentech15
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Space-efficient Verifiable Secret Sharing Using Polynomial Interpolationnexgentechnology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
SPACE-EFFICIENT VERIFIABLE SECRET SHARING USING POLYNOMIAL INTERPOLATIONNexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Secure Data Sharing in Cloud Computing Using Revocable-Storage Identity-Based...Yashwanth Reddy
Presentation on Secure Data Sharing in Cloud Computing Using Revocable-Storage Identity-Based Encryption done at my college during Mini Project Review..
Hope you like it and can be thank me later..
yashkruk@gmail.com
Trust Based Content Distribution for Peer-ToPeer Overlay NetworksIJNSA Journal
In peer-to-peer content distribution the lack of a central authority makes authentication difficult. Without authentication, adversary nodes can spoof identity and falsify messages in the overlay. This enables malicious nodes to launch man-in-the-middle or denial-of-service attacks. In this paper, we present a trust based content distribution for peer-to-peer overlay networks, which is built on the trust management scheme. The main concept is, before sending or accepting the traffic, the trust of the peer must be validated. Based on the success of data delivery and searching time, we calculate the trust index of a node. Then the aggregated trust index of the peers whose value is below the threshold value is considered as distrusted and the corresponding traffic is blocked. By simulation results we show that our proposed scheme achieves increased success ratio with reduced delay and drop.
Identity based proxy-oriented data uploading andKamal Spring
More and more clients would like to store their data to PCS (public cloud servers) along with the rapid development of cloud computing. New security problems have to be solved in order to help more clients process their data in public cloud. When the client is restricted to access PCS, he will delegate its proxy to process his data and upload them. On the other hand, remote data integrity checking is also an important security problem in public cloud storage. It makes the clients check whether their outsourced data is kept intact without downloading the whole data. From the security problems, we propose a novel proxy-oriented data uploading and remote data integrity checking model in identity-based public key cryptography: IDPUIC (identity-based proxy-oriented data uploading and remote data integrity checking in public cloud). We give the formal definition, system model and security model. Then, a concrete ID-PUIC protocol is designed by using the bilinear pairings. The proposed ID-PUIC protocol is provably secure based on the hardness of CDH (computational Diffie-Hellman) problem. Our ID-PUIC protocol is also efficient and flexible. Based on the original client’s authorization, the proposed ID-PUIC protocol can realize private remote data integrity checking, delegated remote data integrity checking and public remote data integrity checking.
Elliptic Curve for Secure Group Key Management in Distributed Networkijceronline
Group communication emphasis an important security criterion in the design of a distributed network. All the members of the group must agree to a common session key. The management of this session key refers to the group key management which is based on some group key agreement protocol. In this paper we propose a group key management method for secure group communication in a distributed network. Frequent change in group membership, and managing the key distribution for new members are the two main problems to be faced in group communication that too with minimal computation and communication overhead. Our system uses the concept of Elliptic curve Cryptography that provide same level of security as that of other cryptosysytems with reduced key size. This results in less re-keying and re-distribution operations, thus reducing computation and communication overheads respectively
Similar to Privacy Preserving Reputation Calculation in P2P Systems with Homomorphic Encryption (20)
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
May_2024 Top 10 Read Articles in Computer Networks & Communications.pdfIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
April 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF Based Intrusion Detection System for Big Data IOT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
A Novel Medium Access Control Strategy for Heterogeneous Traffic in Wireless ...IJCNCJournal
So far, Wireless Body Area Networks (WBANs) have played a pivotal role in driving the development of intelligent healthcare systems with broad applicability across various domains. Each WBAN consists of one or more types of sensors that can be embedded in clothing, attached directly to the body, or even implanted beneath an individual's skin. These sensors typically serve asingle application. However, the traffic generated by each sensor may have distinct requirements. This diversity necessitates a dual approach: tailored treatment based on the specific needs of each traffic typeand the fulfillment of application requirements, such asreliability and timeliness. Never the less, the presence of energy constraints and the unreliable nature of wireless communications make QoS provisioning under such networks a non-trivial task. In this context, the current paper introduces a novel Medium AccessControl (MAC) strategy for the regular traffic applications of WBANs, designed to significantly enhance efficiency when compared to the established MAC protocols IEEE 802.15.4 and IEEE 802.15.6, with a particular focus on improving reliability, timeliness, and energy efficiency.
A Topology Control Algorithm Taking into Account Energy and Quality of Transm...IJCNCJournal
The efficient use of energy in wireless sensor networks is critical for extending node lifetime. The network topology is one of the factors that have a significant impact on the energy usage at the nodes and the quality of transmission (QoT) in the network. We propose a topology control algorithm for software-defined wireless sensor networks (SDWSNs) in this paper. Our method is to formulate topology control algorithm as a nonlinear programming (NP) problem with the objective to optimizing two metrics, maximum communication range, and desired degree. This NP problem is solved at the SDWSN controller by employing the genetic algorithm (GA) to determine the best topology. The simulation results show that the proposed algorithm outperforms the MaxPower algorithm in terms of average node degree and energy expansion ratio.
Multi-Server user Authentication Scheme for Privacy Preservation with Fuzzy C...IJCNCJournal
The integration of artificial intelligence technology with a scalable Internet of Things (IoT) platform facilitates diverse smart communication services, allowing remote users to access services from anywhere at any time. The multi-server environment within IoT introduces a flexible security service model, enabling users to interact with any server through a single registration. To ensure secure and privacy preservation services for resources, an authentication scheme is essential. Zhao et al. recently introduced a user authentication scheme for the multi-server environment, utilizing passwords and smart cards, claiming resilience against well-known attacks. This paper conducts cryptanalysis on Zhao et al.'s scheme, focusing on denial of service and privacy attacks, revealing a lack of user-friendliness. Subsequently, we propose a new multi-server user authentication scheme for privacy preservation with fuzzy commitment over the IoT environment, addressing the shortcomings of Zhao et al.'s scheme. Formal security verification of the proposed scheme is conducted using the ProVerif simulation tool. Through both formal and informal security analyses, we demonstrate that the proposed scheme is resilient against various known attacks and those identified in Zhao et al.'s scheme.
Advanced Privacy Scheme to Improve Road Safety in Smart Transportation SystemsIJCNCJournal
In -Vehicle Ad-Hoc Network (VANET), vehicles continuously transmit and receive spatiotemporal data with neighboring vehicles, thereby establishing a comprehensive 360-degree traffic awareness system. Vehicular Network safety applications facilitate the transmission of messages between vehicles that are near each other, at regular intervals, enhancing drivers' contextual understanding of the driving environment and significantly improving traffic safety. Privacy schemes in VANETs are vital to safeguard vehicles’ identities and their associated owners or drivers. Privacy schemes prevent unauthorized parties from linking the vehicle's communications to a specific real-world identity by employing techniques such as pseudonyms, randomization, or cryptographic protocols. Nevertheless, these communications frequently contain important vehicle information that malevolent groups could use to Monitor the vehicle over a long period. The acquisition of this shared data has the potential to facilitate the reconstruction of vehicle trajectories, thereby posing a potential risk to the privacy of the driver. Addressing the critical challenge of developing effective and scalable privacy-preserving protocols for communication in vehicle networks is of the highest priority. These protocols aim to reduce the transmission of confidential data while ensuring the required level of communication. This paper aims to propose an Advanced Privacy Vehicle Scheme (APV) that periodically changes pseudonyms to protect vehicle identities and improve privacy. The APV scheme utilizes a concept called the silent period, which involves changing the pseudonym of a vehicle periodically based on the tracking of neighboring vehicles. The pseudonym is a temporary identifier that vehicles use to communicate with each other in a VANET. By changing the pseudonym regularly, the APV scheme makes it difficult for unauthorized entities to link a vehicle's communications to its real-world identity. The proposed APV is compared to the SLOW, RSP, CAPS, and CPN techniques. The data indicates that the efficiency of APV is a better improvement in privacy metrics. It is evident that the AVP offers enhanced safety for vehicles during transportation in the smart city.
DEF: Deep Ensemble Neural Network Classifier for Android Malware DetectionIJCNCJournal
Malware is one of the threats to security of computer networks and information systems. Since malware instances are available sufficiently, there is increased interest among researchers on usage of Artificial Intelligence (AI). Of late AI-enabled methods such as machine learning (ML) and deep learning paved way for solving many real-world problems. As it is a learning-based approach, accumulated training samples help in improving thequality of training and thus leveraging malware detection accuracy. Existing deep learning methods are focusing on learning-based malware detection systems. However, there is need for improving the state of the art through ensemble approach. Towards this end, in this paper we proposed a framework known as Deep Ensemble Framework (DEF) for automatic malware detection. The framework obtains features from training samples. From given malware instance a grayscale image is generated. There is another process to extract the opcode sequences. Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) techniques are used to obtain grayscale image and opcode sequence respectively. Afterwards, a stacking ensemble is employed in order to achieve efficient malware detection and classification. Malware samples collected fromthe Internet sources and Microsoft are used for theempirical study. An algorithm known as Ensemble Learning for Automatic Malware Detection (EL-AML) is proposed to realize our framework. Another algorithm named Pre-Process is proposed to assist the EL-AML algorithm for obtaining intermediate features required by CNN and LSTM.Empirical study reveals that our framework outperforms many existing methods in terms of speed-up and accuracy.
High Performance NMF based Intrusion Detection System for Big Data IoT TrafficIJCNCJournal
With the emergence of smart devices and the Internet of Things (IoT), millions of users connected to the network produce massive network traffic datasets. These vast datasets of network traffic, Big Data are challenging to store, deal with and analyse using a single computer. In this paper we developed parallel implementation using a High Performance Computer (HPC) for the Non-Negative Matrix Factorization technique as an engine for an Intrusion Detection System (HPC-NMF-IDS). The large IoT traffic datasets of order of millions samples are distributed evenly on all the computing cores for both storage and speedup purpose. The distribution of computing tasks involved in the Matrix Factorization takes into account the reduction of the communication cost between the computing cores. The experiments we conducted on the proposed HPC-IDS-NMF give better results than the traditional ML-based intrusion detection systems. We could train the HPC model with datasets of one million samples in only 31 seconds instead of the 40 minutes using one processor), that is a speed up of 87 times. Moreover, we have got an excellent detection accuracy rate of 98% for KDD dataset.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
IoT Guardian: A Novel Feature Discovery and Cooperative Game Theory Empowered...IJCNCJournal
Cyber intrusion attacks increasingly target the Internet of Things (IoT) ecosystem, exploiting vulnerable devices and networks. Malicious activities must be identified early to minimize damage and mitigate threats. Using actual benign and attack traffic from the CICIoT2023 dataset, this WORK aims to evaluate and benchmark machine-learning techniques for IoT intrusion detection. There are four main phases to the system. First, the CICIoT2023 dataset is refined to remove irrelevant features and clean up missing and duplicate data. The second phase employs statistical models and artificial intelligence to discover novel features. The most significant features are then selected in the third phase based on cooperative game theory. Using the original CICIoT2023 dataset and a dataset containing only novel features, we train and evaluate a variety of machine learning classifiers. On the original dataset, Random Forest achieved the highest accuracy of 99%. Still, with novel features, Random Forest's performance dropped only slightly (96%) while other models achieved significantly lower accuracy. As a whole, the work contributes substantial contributions to tailored feature engineering, feature selection, and rigorous benchmarking of IoT intrusion detection techniques. IoT networks and devices face continuously evolving threats, making it necessary to develop robust intrusion detection systems.
** Connect, Collaborate, And Innovate: IJCNC - Where Networking Futures Take ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Enhancing Traffic Routing Inside a Network through IoT Technology & Network C...IJCNCJournal
IoT networking uses real items as stationary or mobile nodes. Mobile nodes complicate networking. Internet of Things (IoT) networks have a lot of control overhead messages because devices are mobile. These signals are generated by the constant flow of control data as such device identity, geographical positioning, node mobility, device configuration, and others. Network clustering is a popular overhead communication management method. Many cluster-based routing methods have been developed to address system restrictions. Node clustering based on the Internet of Things (IoT) protocol, may be used to cluster all network nodes according to predefined criteria. Each cluster will have a Smart Designated Node. SDN cluster management is efficient. Many intelligent nodes remain in the network. The network design spreads these signals. This paper presents an intelligent and responsive routing approach for clustered nodes in IoT networks. An existing method builds a new sub-area clustered topology. The Nodes Clustering Based on the Internet of Things (NCIoT) method improves message transmission between any two nodes. This will facilitate the secure and reliable interchange of healthcare data between professionals and patients. NCIoT is a system that organizes nodes in the Internet of Things (IoT) by grouping them together based on their proximity. It also picks SDN routes for these nodes. This approach involves selecting one option from a range of choices and preparing for likely outcomes problem addressing limitations on activities is a primary focus during the review process. Predictive inquiry employs the process of analyzing data to forecast and anticipate future events. This document provides an explanation of compact units. The Predictive Inquiry Small Packets (PISP) improved its backup system and partnered with SDN to establish a routing information table for each intelligent node, resulting in higher routing performance. Both principal and secondary roads are available for use. The simulation findings indicate that NCIoT algorithms outperform CBR protocols. Enhancements lead to a substantial 78% boost in network performance. In addition, the end-to-end latency dropped by 12.5%. The PISP methodology produces 5.9% more inquiry packets compared to alternative approaches. The algorithms are constructed and evaluated against academic ones.
Multipoint Relay Path for Efficient Topology Maintenance Algorithm in Optimiz...IJCNCJournal
The Optimal Link State Routing (OLSR) protocol employs multipoint relay (MPR) nodes to disseminate topology control (TC) messages, enabling network topology discovery and maintenance. However, this approach increases control overhead and leads to wasted network bandwidth in stable topology scenarios due to fixed flooding periods. To address these challenges, this paper presents an Efficient Topology Maintenance Algorithm (ETM-OLSR) for Enhanced Link-State Routing Protocols. By reducing the number of MPR nodes, TC message generation and forwarding frequency are minimized. Furthermore, the algorithm selects a smaller subset of TC messages based on the changes in the MPR selection set from the previous cycle, adapting to stable and fluctuating network conditions. Additionally, the sending cycle of TC messages is dynamically adjusted in response to network topology changes. Simulation results demonstrate that the ETM-OLSR algorithm effectively reduces network control overhead, minimizes end-to-end delay, and improves network throughput compared to traditional OLSR and HTR-OLSR algorithms.
Online blood donation management system project.pdfKamal Acharya
Blood Donation Management System is a web database application that enables the public to make online session reservation, to view nationwide blood donation events online and at the same time provides centralized donor and blood stock database. This application is developed
by using ASP.NET technology from Visual Studio with the MySQL 5.0 as the database management system. The methodology used to develop this system as a whole is Object Oriented Analysis and Design; whilst, the database for BDMS is developed by following the steps in Database Life Cycle. The targeted users for this application are the public who is eligible to donate blood ,'system moderator, administrator from National Blood Center and the staffs who are working in the blood banks of the participating hospitals. The main objective of the development of this application is to overcome the problems that exist in the current system, which are the lack of facilities for online session reservation and online advertising on the nationwide blood donation events, and also decentralized donor and blood stock database. Besides, extra features in the system such as security protection by using password, generating reports, reminders of blood stock shortage and workflow tracking can even enhance the efficiency of the management in the blood banks. The final result of this project is the development of web database application, which is the BDMS.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
A case study of cinema management system project report..pdfKamal Acharya
A computer reservation system or central reservation system is a computerized system used to store and retrieve information and conduct transactions related to air travel, hotels, car rental, or activities. These systems typically allow users to book hotel rooms, rental cars, airline tickets as well as activities and tours. They also provide access to railway reservations and bus reservations in some markets, although these are not always integrated with the main system. For these systems to be accessible on mobile phones and computers outside the premises of the airport, cinema, train station or stadiums, they need to be on the internet or a network.
This project focuses on the design and implementation of a web based cinema management system for the allocation of seat tickets online. The system would feature the registration of users, use of serial numbers and pins gotten from scratch cards sold and a printed slip. The system would have a store of all the seats and automate the generation of fresh serial numbers and pins.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
This document is by explosives industry in which document discussed manufacturing process and flow charts details by nitric acid and sulfuric acid and tetra benzene and step by step details of explosive industry explosives industry is produced raw materials and manufacture it by manufacturing process
Fruit shop management system project report.pdfKamal Acharya
The export maintenance system is a fully featured application that can help we manage fruit delivery business and achieve more control and information at a very low cost of total ownership.
A fruit export maintains automatically monitors purchase, sales, supplier information. The system includes receiving fruit from the different supplier. Customer order is placed in the system, based on the order fruit has been sales to the customer.
The report contains the details about product, purchase, sales, stock, and invoice. The main objective of this project is to computerize the company activities and to provide details about the production process at the fruit export maintenance system.
The demand of fresh fruit fruits and processed food items in international and domestic market has shown a decent increase. This estimation is creating a necessity for growing more and more fruit fruits to cater the growing demand of domestic & international market.
The customers effectively and hence help for establishing good relation between customer and fruit shop organization. It contains various customized modules for effectively maintaining fruit and stock information accurately and safely.
When the fruits are sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting fruits for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
The proposed project is developed to manage the fruit shop in the fruits for shop. The first module is the login. The admin should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Final project report on grocery store management system..pdf
Privacy Preserving Reputation Calculation in P2P Systems with Homomorphic Encryption
1. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
Privacy Preserving Reputation Calculation in
P2P Systems with Homomorphic Encryption
FUJITA Satoshi
Graduate School of Advanced Science and Engineering, Hiroshima
University, Kagamiyama 1-4-1, Higashi-Hiroshima, 739-8527, Japan
Abstract. In this paper, we consider the problem of calculating the node reputation in a Peer-to-
Peer (P2P) system from fragments of partial knowledge concerned with the trustfulness of nodes
which are subjectively given by each node (i.e., evaluator) participating in the system. We are
particularly interested in the distributed processing of the calculation of reputation scores while
preserving the privacy of evaluators. The basic idea of the proposed method is to extend the
EigenTrust reputation management system with the notion of homomorphic cryptosystem. More
specifically, it calculates the main eigenvector of a linear system which models the trustfulness
of the users (nodes) in the P2P system in a distributed manner, in such a way that: 1) it blocks
accesses to the trust value by the nodes to have the secret key used for the decryption, 2) it improves
the efficiency of calculation by offloading a part of the task to the participating nodes, and 3) it
uses different public keys during the calculation to improve the robustness against the leave of
nodes. The performance of the proposed method is evaluated through numerical calculations.
Keywords: P2P reputation management, homomorphic cryptosystem, EigenTrust, Paillier cryp-
tosystem.
1 Introduction
Reputation management is a crucial task for fully distributed systems such as Peer-
to-Peer (P2P) systems and federated social networks since in those systems, services
are provided by individual, unauthorized peers (i.e., nodes) unlike classical server-
based systems. The reputation of nodes is used not only to find high quality services
as in gourmet sites, but also to identify low quality service-providers to penalize
them by deliberately reducing the service quality supplied to them. Indeed, many
P2P systems support reputation management as a part of the incentive mechanism,
so as to encourage nodes to increase their reputation by improving the service
quality supplied by those nodes.
The reputation of a node in such systems is generally calculated from trust
value of nodes given by entities called evaluators (e.g., customers in the case of
online shopping site). Therefore, the trust value can be an obvious target of attacks
by malicious nodes who wish to Illegally raise their reputation. One way to protect
such attacks is to ask trustworthy third parties to calculate trust value of the
evaluatee and to keep it securely, where if trust values calculated by different entities
DOI: 10.5121/ijcnc.2021.13601 1
2. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
conflict, an agreement could be achieved through majority voting. Such a consign-
based approach would work well if the trust value of a node can be (automatically)
generated in an objective manner, as in cases in which the contribution of an amount
of upload bandwidth in parallel download systems such as BitTorrent and the
forwarding of received video streams in video streaming systems such as seedess1
and P2PSP2 (if the credibility of the prepared server is questionable, we could
record the history of contributions and reputation calculations as a blockchain, so
that the recorded information can be verified by all nodes involved in the service).
In this paper, we consider a more general setting for the reputation management
in P2P systems in which the trust value of an evaluatee is given by an evaluator
in a subjective manner and the evaluator wishes to keep it secret from other nodes
including the evaluatee (e.g., the reader could consider the personnel evaluation
in an organization such as company and alumni meeting). To the author’s best
knowledge, existing reputation management schemes for P2P systems do not take
such situations into account at all and do not adequately preserve the privacy of the
evaluators. In this paper, we tackle this challenging issue, and propose a method
to calculate the reputation of each node in a distributed manner without disclosing
any subjective trust value, with the aid of homomorphic encryption.
There are a lot of previous work concerned with the privacy preserving cal-
culations with homomorphic encryption [11–13, 16]. Most of them assume that a
trustworthy third party is commissioned to conduct the calculation on confidential
data stored in a cloud server, which is encrypted with the public key of an appro-
priate key server. Thus, it implicitly allows the trustworthy key server to decrypt
the data even if it was strictly confidential.
Such a centralized approach, however, does not work well in P2P systems for
the following reasons. At first, such calculations should be realized so as to block
accesses to the trust values by a node which has the secret key for the decryption.
Specifically, although it could access the ciphertext of the reputation score which
is the final result of calculation, it should not be allowed to access any data from
which the original trust value of nodes could be inferred. Concerned with this issue,
in the proposed method, we take an approach so that encrypted reputation values
are successively updated through calculation to reflect the trust value of individual
nodes. Although the intermediate results of the calculation are shared by all nodes,
the (original) trust values cannot be guessed from them besides the fact that the
sum of trust values given by an evaluator equals to a certain fixed value. The sec-
ond point we need to consider is the decentralization of the reputation calculation.
Existing privacy preserving schemes are designed for the bulk processing in which
a central entity conducts the calculation on the data stored on a cloud server. In
contrast, the data on P2P systems, including trust values, are distributed over the
1
https://seedess.com/
2
https://p2psp.org/
2
3. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
network from the beginning, and it is not efficient to aggregate them to a central-
ized server before starting the calculation. In addition, the calculation time can
significantly be reduced by utilizing the computational resources of the participat-
ing nodes. In this aspect, the proposed method incorporates several techniques to
improve the efficiency of the distributed processing. The third point is that due to
node churn, it is not guaranteed that a node holding the secret key will stay in
the system at the time of decryption. To overcome this issue, we use different pub-
lic keys for the reputation calculation. The effectiveness of the proposed method is
evaluated by conducting numerical calculations. The results show that the proposed
method reduces the maximum circulation time used for aggregating the result of
multiplications to a half, thereby reducing the time required for each round of the
reputation computation, and the cost of privacy preservation is proportional to the
number of nodes N, which takes about 16 seconds when N = 1024.
The remainder of this paper is organized as follows. Section 2 overviews related
work. Section 3 reviews the EigenTrust reputation management system which plays
a central role in the proposed method. Section 4 describes the details of the pro-
posed method. Section 5 summarizes the results of evaluations. Finally, Section 6
concludes the paper with future work.
2 Related Work
2.1 Homomorphic Encryption
Homomorphic encryption (HE, for short) is a type of encryption which preserves
the homomorphism for certain arithmetic operations3 and is classified into several
types by the strength of preservations, such as partially homomorphic, somewhat
homomorphic, leveled fully homomorphic, and fully homomorphic. The concept of
HE was initially proposed by Rivest in 1978 [14]. Although the concrete realization
of HE has been an open issue for thirty years, it was positively answered by Craig
Gentry in 2009 [5] with the proposal of a fully homomorphic cryptosystem based
on the lattice-based cryptography.
As a tool available to developpers who are not a specialist in cryptography,
IBM released a C++ library named HElib[6]4, which is being updated actively.
The current version of HElib adopts the Brakerski-Gentry-Baikuntanathan (BGV)
method and the Cheon-Kim-Kim-Song (CKKS) method, which are extentions of
the Gentry’s method. The number of options available for the implementation of
security systems dramatically increases if we do not stick to be fully homomorphic.
3
Homomorphism in the context of HE implies the property such that the decryption of the
result of an operation applied to ciphertexts is consistent with the result applied to the original
plaintexts.
4
https://github.com/homenc/HElib
3
4. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
Table 1. Execution time required for the encoding/decoding in the Paillier cryptosystem. Two
values in each cell show the mean and the sample standard deviation over 1000 runs, respectively.
Bit length Key generation [ms] Encoding [ms] Decoding [ms]
1024 19.32 7.72 (0.67) 7.64 (0.69)
2048 27.41 7.65 (0.59) 7.57 (0.63)
4096 641.58 47.54 (3.62) 47.29 (3.72)
8192 12782.64 273.42 (16.83) 272.87 (16.50)
In fact, it is widely known that RSA and ElGamal5 are multiplicative HE, and
Goldwasser-Micali and Paillier [10] are additive HE, where the last one is the main
player of the current paper. A typical application for additive HEs is the electronic
voting, as it merely needs simple counting of votes. Other applications of additive
HEs include the analysis of medical data [1] and the k-clustering of vector data
[18]. A formal definition of the Paillier cryptosystem is given in Appendix to make
this paper self contained, and before proceeding to the detailed explanation of the
proposed method, as a preliminary experiment, we evaluated the execution time
of a Python program written with the paillierlib library on a computer with Intel
Core i9, 2.3 GHz, and 16 GB memory. Table 1 summarizes the results, where the
key length is varied from 1024 bits to 8192 bits. From the table, we find that when
the key length is 2048 bits, encoding and decoding operations can be done in 10
ms each, confirming that the Paillier cryptosystem can be used as a tool for the
privacy preserving calculations.
2.2 Related Work on Reputation Management
In the literature, there are many proposals concerned with the reputation manage-
ment in P2P systems. PeerTrust [15] is designed for the transaction-based feedback
system and calculates the reputation of each node by considering three basic trust
parameters and two adaptive factors, which include the amount of feedback received
from other nodes, the number of transactions relevant to the node, the credibility
of the source of feedback, and the context of transactions and the community.
PowerTrust [17] takes advantage of the distribution of evaluations among nodes,
which is generally not uniform but follows a power-law. Specifically, it adaptively
selects a small number of nodes with the highest reputation, and leverages them to
significantly improve the accuracy of calculation and the speed of convergence.
Although a detailed explanation of EigenTrust will be given in the next section,
we could overview several proposals relevant to EigenTrust, as follows. Choi et al. [3]
proposed Enhanced Eigentrust, which uses a beta distribution to calculate the nor-
malized trust values. The intensive employment of trusted nodes effectively speed
up the convergence in calculating reputation values. Personalized EigenTrust [2]
5
ElGamal cryptosystem is a public-key cryptosystem whose difficulty is based on the discrete
logarithm problem.
4
5. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
allows each node to individually specify its trusted nodes and the method proposed
in [4] recognizes such trusted nodes with the aid of Page Rank. Federated Eigen-
Trust [7] introduces the notion of representative nodes to manage the unpredictable
leave of trusted nodes. HonestPeer [9] offloads the task of reputation calculation to
(honest) nodes with high ratings to legitimately increase the reputation of nodes.
3 Reputation Calculation with EigenTrust
EigenTrust provides a method to calculate the (global) reputation value of each
node in a P2P system based on the (local) trust value given by each node to other
nodes. Note that such a collection of trust values can be represented in the form of
a square matrix. In the following, we assume that the trust value cij given by node
i for j is normalized to the [0, 1] interval so that the higher the value, the higher
the trust level6. It is natural to assume that the value of cjk is trustable for i, if
cij is sufficiently large (each node is assumed to have absolute trust in itself and
cii = 1 holds for any i). In other words, we could assume the existence of a sort of
transitivity concerned with the trust. By extending this idea, given a collection of
local trust values, the reputation tik of i in k could be represented as
tik :=
n
∑
j=1
cijcjk.
In other words, we have
ti1
ti2
.
.
.
tin
:=
c11 c21 · · · cn1
c12 c22 · · · cn2
.
.
.
.
.
.
.
.
.
c1n c2n · · · cnn
ci1
ci2
.
.
.
cin
= (⃗
c1,⃗
c2, · · · ,⃗
cn)⃗
ci = C⃗
ci,
where ⃗
ci = (ci1, . . . , cin)T . Although the above ⃗
ti = (ti1, ti2, . . . , tin)T is the repu-
tation of nodes through a chain of length two from i, it can be easily extended to
the chain of length n so that ⃗
ti := Cn⃗
ci. Vector ⃗
ti is known to converge to the main
eigenvector of matrix C as n → ∞ (i.e., to the eigenvector such that the eigenvalue
is one) regardless of the value of ci, as long as matrix C is irreducible and acyclic,
and the existence of such an eigenvector is guaranteed by the Peron Frobenius
Theorem. It is worth noting that ⃗
t = limn→∞ Cn⃗
c corresponds to the stationary
distribution of Markov chain in such a way that the transition probability between
states is given by C. Although such ⃗
t can be obtained algebraically by solving the
6
In this setting, we could not distinguish between not trusting j and not having an opinion about
j.
5
6. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
eigenvalue equation C⃗
t = ⃗
t, since the computational complexity increases as n in-
creases, it is common to solve this equation numerically by repeatedly multiplying
C to an appropriate initial vector.
4 Proposed Method
There are several options to apply the notion of homomorphic cryptosystem to
the reputation management in EigenTrust. One possible idea is to encrypt trust
value cij and to multiply it with ei after collecting encrypted values from all nodes.
However, such a naive approach does not scale since it forces the central entity to
conduct all multiplications, and is less efficient than a simple centralized approach
in which all encrypted cij’s are collected to the server before starting the calculation.
Thus in the following, we will focus our attention on another approach in which
the encryption is applied to reputation vector ⃗
e.
4.1 Baseline
At first, we consider a simple client-server (C/S) scheme, which will be used as
the baseline in the proposed method. In this scheme, a central server manages
the encrypted vector ⃗
e = (e1, e2, . . . , en) and repeats the following steps until ⃗
e
converges to a certain reputation vector:
1. For each i, the server sends ei to client i;
2. Client i calculates ηj := ei × cij for all j, and replies the result to the server;
and
3. After receiving encrypted values from all clients, the server updates ⃗
e as ei :=
∑
j ηj for each i.
Note that since the fact of cij = 0 is hidden by applying the encryption, exactly n2
multiplications should be conducted even if the given matrix is sparse, unless the
fact of cij = 0 is notified to the server through alternative route.
Since the role of client i is to receive encrypted ei from the server and to return
the resulting list (ei×ci1, . . . , ei×cin) to the server, if the multiplication is conducted
under the Paillier cryptography, merely the results of multiplications to the trust
values are collected to the server without revealing its own trust values. In addition,
since an updated ei will be received from the server in the next round, two successive
rounds are separated through the barrier synchronization.
4.2 Distributed Aggregation
The above C/S scheme can be extended so that the aggregation of the results is
replaced by the P2P communication. More concretely, we organize the task of ag-
gregating the result of n × n independent multiplications into several task-groups
6
7. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
1 2 3 4 5 6
7 8 9 10 11 12
13 14 15 16 17 18
19 20 21 22 23 24
U1
U2
U3
U4
V1 V2 V3 V4 V5 V6
Fig. 1. Two partitions of the set of nodes V = {1, 2, . . . , 24} with k = 4. Four subsets in U
are represented by dashed blue rectangles and six subsets in V are represented by dashed red
rectangles.
and to give the responsibility of controlling each task-group to a node in V in a
decentralized manner. Note that such an extension of data aggregation still pre-
serves an important nature of the baseline scheme so that each node does not have
to disclose its trust values to the others.
Assume n(= |V |) is not a prime and let k be a divisor of n. At first, we partition
V into n/k subsets of an equal size as V = {Vi : 1 ≤ i ≤ n/k}, and at the same
time, partition V into k subsets of an equal size as U = {Uj : 1 ≤ j ≤ k} (the reader
could imagine two orthogonal partitions naturally realized from a two-dimensional
array of size k × n/k. See Figure 1 for illustration). Let Mi = {ei × cij : 1 ≤ j ≤ n}
be the set of n independent multiplications conducted by node i in the baseline
scheme. We consider a partition of Mi into n/k subsets Mi,1, . . . , Mi,n/k, so that
Mi,y consists of multiplications for nodes j in subset Vy. See Figure 2 for illustration.
Then for each Ux ∈ U, we can organize a collection of task groups in such a way
that the jth task-group consists of the aggregation of the result of multiplications
in
∪
i∈Ux
Mi,j. Since subset Ux consists of n/k nodes, we can assign such n/k task-
groups to the nodes in Ux in one-to-one manner. Let Tx,y be the task-group assigned
to the yth node in subset Ux. Note that the outcome of Tx,y is a collection of results
of k independent inner products of sub-vectors of length n/k each, which are all
conducted by the nodes in subset Ux. Although the total number of multiplications
controlled by a node in Ux does not change even if the value of parameter k is
varied, a too small k increases the number of additions to be conducted at the
centralized server. See Figure 3 for illustration.
The concrete execution of task-group Tx,y proceeds as follows. Suppose that
each node i computes multiplication ei × cij by using encrypted ei received from
7
8. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
1 2 3 4 5 6
7 8 9 10 11 12
13 14 15 16 17 18
19 20 21 22 23 24
U1
U2
U3
U4
M9,1 M9,2 M9,3 M9,4 M9,5 M9,6
Fig. 2. 24 multiplications concerned with node 9 in subset U2 ∈ U. Nodes in U2 are represented
by circles and multiplications conducted by node 9 are represented by simple numbers. Set of
multiplications M9,y, for 1 ≤ y ≤ 6, is indicated by a dashed red rectangle which corresponds to
task group T2,y since node 9 is a member of subset U2.
the central entity, and stores the results locally. The aggregation of those results
is independently done for each j contained in Tx,y by using a chain of length at
most n/k (a part of such chain is indicated by a blue arrow in Figure 3). The
order of nodes in the chain is determined by the responsible node, say i∗, and the
aggregation is realized by flowing a message along the determined route as follows:
At first, the responsible node i∗ sends out ηi∗ := ei∗ × ci∗j to the first node on the
chain. Upon receiving an encrypted value from the predecessor, node i′ adds its
own ei′ × ci′j to the received value, and passes the result to the next node on the
chain, where the last node on the chain returns the result to i∗. The responsible
node i∗ can initiate such a flow on several independent chains if n/k is large, while
in such a case, to prevent the double counting of ηi∗ , node i∗ should send out ηi∗
only for one chain and value 0 for the remaining chains.
4.3 Adaptive Load Balancing
In the above scheme, several messages are circulated along chains in each subset
Ux ∈ U to conduct the partial update of tentative reputation value of nodes in V .
The final reputation vector is obtained by repeating rounds similar to EigenTrust,
and the next round can start only after collecting partial updates from all subsets.
Thus we could speed up the reputation calculation by reducing the maximum cir-
culation time over all chains while keeping the number chains (recall that the C/S
scheme described before trivially achieves the min-max circulation time). In the
proposed method, we realize such a reduction of the maximum circulation time by
using the following two techniques:
8
9. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
22
22
22
22
22
22
M7
M12
M11
M10
M9
M8
Fig. 3. Aggregation of the result of multiplications through circulating an aggregation massage.
In this figure, each layer corresponds to n multiplications conducted by a node in U2, where the
results for node 22 are placed at the same location in each layer. Thus, the result of partial inner
product of length n/k can be obtained by aggregating the result of n/k multiplications conducted
by six nodes in U2.
– Organize U so that each subset Ux in the partition consists of nodes whose
mutual distance is short.
– The responsible node i∗ monitors the circulation time of each chain managed
by i∗, and re-organize the collection of chains so that the maximum circulation
time could be minimized.
A typical realization of the first technique is to measure the round-trip time for
each pair of nodes in V beforehand, and to apply the k-means method to obtain
a collection of k subsets. On the other hand, the second technique can be realized
by adaptively applying split and merge operations to the collection of chains in
such a way that: 1) a chain with long circulation time is split into two chains and
2) two chains of small circulation time are merged into a chain. Note that if the
partition U obtained by the first technique reflects the proximity of the nodes, we
could assume that the transmission time to the next node on any chain derived
from U is bounded by a sufficiently small value such as 50ms, and given such a
subset of nodes, the second technique manages the difference of response time due
to the overload of nodes.
4.4 Improve the Resilience Against Churn
In the previous description, we assumed that each element of the reputation vector
is encrypted using the public key of the central key server, but this assumption can
be relaxed as follows:
– Different keys can be used for each round, if it is allowed to decrypt the repu-
tation vector after each round.
9
10. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
Central server
Responsible node A Responsible node B
Task group Tx,y Task group Tx’,y’
Request for decryption
Ciphertext of ej encrypted
with public key of B
Plaintext of partially
updated ej
Reflecting the local trust
values for node j to the
accumulated value
Fig. 4. The flow of reputation calculation in a round. Although only two task groups are illustrated
in this figure, there are n(= k ×n/k) task-groups in the system each of which aggregates the result
of n multiplications. Note that the central server is used to collect the resulting reputation scores
and the actual calculation is offloaded to the participants.
– Different keys can be used for each task group.
– The key used to decrypt the outcome of a task group does not have to be held
by the responsible node of the task group. In fact, the task of decryption can
be delegated to the responsible node of other task group.
With such a refinement, the description of the overall task group is modified as
follows (see Figure 4 for illustration):
1. The responsible node i∗ of a task group receives the tentative reputation value
of each member from the server, and encrypts them using the public key of
the node which is responsible for the decryption, or the server conducts the
encryption before sending it to node i∗.
2. The responsible node i∗ sends the encrypted tentative reputation value to each
member in the subset, conducts the partial aggregation under its control, and
forwards the resulting list to the node responsible for decryption, where the
resulting list contains n elements.
3. After receiving a list to be descrypted, the node decrypts each element in the
list, and returns the result to the central server.
In the above extension, the grouping of nodes causes no load balancing effect at all
but increases the total load of the nodes since each responsible node must decrypt a
10
11. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
list of length n every round. Instead, the content of calculations in each task group
is kept secret from the server and members of other subsets, which increases the
level of privacy preserving compared to the C/S scheme. In addition, by delegating
the task of decryption to the members of other subset, we could preserve the privacy
of each member from other members in the same group including the responsible
node i∗. Finally, since the role of key holders is only to decrypt the result of a task
group in a certain round, it can be easily replaced by other node in each round,
thereby increasing the resilience against node churn.
5 Evaluation
In this section, we evaluate the performance of the proposed method, in terms
of: 1) the effect of acceleration of the data aggregation and 2) the amount of ad-
ditional cost due to privacy preservation in P2P environment through numerical
calculations. More specifically, as for the first point,
– We evaluate how much the circulation of aggregation message can be accelerated
by using the k-means clustering and a heuristic minimization of the length of
the cyclic route, by assuming that nodes are associated with a point in the
three-dimensional Euclidean space, and
– We evaluate how much the maximum circulation time over all clusters can be
reduced by reflecting the variance of the response time of nodes, by assuming
that the response time follows a geometric distribution.
The reader should note that the node density around a node becomes sparse as
the number of dimensions increases, which contradicts to the intuition such that
the locality of nodes plays a crucial role in organizing efficient P2P overlay, and
if the dimension is fixed to two, it becomes difficult to reflect the diversity of the
locality existing in real-world networks. On the other hand, the slow-down due to
privacy preservation will be estimated in Section 5.2 using the result of preliminary
experiments summarized in Table 1.
5.1 Effect of Reflecting the Locality of Nodes
At first, we evaluate the effect of the k-means clustering to reduce the maximum cir-
culation time (over all subsets) by assuming that each responsible node determines
the cyclic route in a random manner. Figure 1 summarizes the results. The vertical
axis indicates the ratio of the maximum circulation time obtained by the k-means
method to the value obtained by applying a random partitioning (into subsets with
an equal number of nodes), and the height of each bar represents the value averaged
over 100 random instances generated for each combination of the number of nodes
N and the number of clusters k. We confirm that no instance yields a ratio worse
than 1.0, and if k ≥ 8, the k-means clustering reduces the maximum circulation
11
12. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
512 1024 2048 4096 8192
Number of Nodes
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Ratio
of
Maximum
Circulation
Time
Efect of k-Means Clustering Compared with Random Partitioning
k=4
k=8
k=16
k=32
k=64
k=128
Fig. 5. Speed-up of the aggregation time by the k-means clustering compared with a random
clustering into subsets of an equal size.
time of the random partitioning to almost a half, on average. Such a significant
reduction should be caused by the short average distance in the resulting clusters,
since the cluster size obtained by the k-means method is not necessarily equal (i.e.,
the maximum cluster size is larger than the random partitioning). To clarify this
point, we evaluated the maximum average distance over all subsets generated by
two schemes. Figure 6 summarizes the results. The average distance realized by
the random partitioning gradually increases as k increases, which is because we are
taking the maximum circulation time over k subsets. In the k-means method, on
the other hand, since the effect of localization increases for larger k’s, the ratio to
the random partitioning becomes smaller than the ratio indicated in Figure 5 (e.g.,
the ratio is less than 0.25 for k = 256).
Next, we evaluate the effect of circulation order to the aggregation time, which
is optimized in the proposed method by using an approximation scheme based on
the minimum spanning tree (MST). As the result of experiments, we confirmed
that although the length of the cycle, i.e., summation of the edge weights, realized
by a random ordering increases in proportion to the number of nodes in the cluster,
the cycle length realized by the proposed method increased about 1.58 times when
12
13. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
4 8 16 32 64 128 256
Cluster size K
0
10
20
30
40
50
60
70
Average
distance
among
nodes
within
a
cluater
[ms]
Maximum average distance over all clusters (N=8192)
k-means
random
Fig. 6. Maximum average distance over all clusters.
the cluster size doubled, on average. This value of 1.58 is roughly in line with the
degree of increase in the weight of the MST for the given instance. In fact, while it
is well known that the theoretical upper bound on the approximation ratio of the
MST-based approximation scheme is 2.0, it was experimentally confirmed that the
length of approximated solution covering randomly placed points in a 3D cube is,
1.2 to 1.3 times the weight of the MST (this ratio is slowly worsened as the number
of nodes increases). In terms of the real-time, the above result roughly corresponds
to the situation in which the aggregation time of 17 seconds taken by the random
ordering reduces to about 4 seconds by the proposed method, when N = 512.
The effect of the load balancing reflecting the variance of the response time of
nodes is evaluated as follows. In this experiment, we consider a theoretical model
in which the response time of each node follows a geometric distribution with prob-
ability p. Then, we evaluated to what extent the maximum sum of the response
times over all subsets can be reduced by using a greedy partitioning scheme instead
of a random partitioning, by varying the number of nodes N and the probability p
(note that the smaller p is, the mean and the variance of the response times become
larger). The results are summarized in Figure 7. We confirm that as N increases,
13
14. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
64 128 256 512 1024 2048
Number of Nodes in a Cluster
0.91
0.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
Ratio
of
Accumulated
Response
Time
to
the
Randomized
Scheme Effect of Greedy Load Balancing
p=0.5
p=0.3
p=0.1
p=0.01
Fig. 7. Effect of load balancing by the greedy scheme.
the room for the improvement by the greedy scheme becomes smaller since the bad-
ness of the random partitioning will be amortized. However, even with N = 128,
we can obtain a speed-up of more than 4% for any p ≤ 0.5.
5.2 Cost of Privacy Preservation
Finally, we evaluate the increase of the computation time due to the enhancement
of privacy preservation. In the baseline method, encryption is conducted only once
at the beginning of computation and decryption is conducted only once when the
final reputation value is obtained. In the enhanced method, on the other hand,
encryption and decryption are conducted for all reputation values with different
keys in each round to prevent other nodes from eavesdropping the trust values.
Thus, the additional overhead per round can be estimated as the time required
to encrypt/decrypt one element multiplied by the number of elements. The results
in Table 1 imply that when the number of elements is N, the time required for
encryption and decryption is 7.65N [ms] and 7.57N [ms], respectively; e.g., when
N = 1024, it takes about 8 seconds for encryption and decryption, respectively.
14
15. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
Note that this cost can be mitigated by conducting the encryption/decryption once
every few rounds, rather than every round.
6 Concluding Remarks
In this paper, we propose a method to extend the EigenTrust reputation manage-
ment system with the notion of homomorphic cryptosystem so that the privacy
of evaluations is protected from other nodes. Experimental results show that the
proposed method reduces the maximum circulation time used for aggregating the
result of multiplications to a half, thereby reducing the time required for each round
of the reputation computation, and the cost of privacy preservation is proportional
to the number of nodes N, which takes about 16 seconds when N = 1024. A future
work is to implement the proposed method in existing P2P systems.
Conflicts of Interest
The author declares no conflict of interest.
References
1. A. Ara, M. Al-Rodhaan, Y. Tian, and A. Al-Dhelaan. A secure privacy-preserving data
aggregation scheme based on bilinear ElGamal cryptosystem for remote health monitoring
systems. IEEE Access, 5, pp. 12601–12617, 2017.
2. N. Chiluka, N. Andrade, D. Gkorou, and J. Pouwelse. Personalizing EigenTrust in the Face of
Communities and Centrality Attack. in Proc. IEEE 26th Int’l Conf. on Advanced Information
Networking and Applications, 2012.
3. D. Choi, S. Jin, Y. Lee, and Y. Park. Personalized eigentrust with the beta distribution.
ETRI Journal, 32(2):348–350, 2010.
4. P. A. Chirita, W. Nejdl, M. T. Schlosser, and O. Scurtu. Personalized Reputation Manage-
ment in P2P Networks. in Proc. ISWC Workshop on Trust, Security, and Reputation on the
Semantic Web, 2004.
5. C. Gentry. Fully Homomorphic Encryption Using Ideal Lattices. in Proc. the 41st ACM
Symposium on Theory of Computing (STOC), 2009.
6. S. Halevi and V. Shoup. Algorithms in HElib. In Proc. CRYPTO 2014: Advances in Cryp-
tology, 2014, pages 554–571.
7. R. Jansen, T. Kaminski, F. Korsakov, A. S. Croix, and D. Selifonov. A Priori Trust Vulner-
abilities in EigenTrust. Technical report, University of Minnesota, 2008.
8. S.D. Kamvar, M.T. Schlosser, H. Garcia-Molina. The Eigentrust algorithm for reputation
management in P2P networks. in Proc. 12th Int’l Conf. on World Wide Web (WWW ’03),
2003, pages 640–651.
9. H. A. Kurdi. HonestPeer: An enhanced EigenTrust algorithm for reputation management in
P2P systems. Journal of King Saud University – Computer and Information Sciences (2015)
27, 315–322.
10. P. Paillier. Public-Key Cryptosystems Based on Composite Degree Residuosity Classes. in
Proc. EUROCRYPT 1999, pages 223–238.
11. M. M. Potey, C. A. Dhote, and D. H. Sharma. Homomorphic encryption applied to the cloud
computing security. Procedia Computer Science, 79, pp. 175–181, 2016.
15
16. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
12. M. Tebaa, S. E.Hajji, and A. E. Ghazi. Homomorphic encryption method applied to Cloud
Computing in Proc. National Days of Network Security and Systems, 2012.
13. M. Tebaa and S. E. Hajji. Secure cloud computing through homomorphic encryption. Com-
puter Science, ArXiv, Corpus ID: 21074700, 2014.
14. R. L. Rivest, L. Adleman, and M. L. Dertouzos. On data banks and privacy homomorphisms.
In Foundations of Secure Computation, 1978.
15. L. Xiong and L. Liu. PeerTrust: supporting reputation-based trust for node-to-node electronic
communities. IEEE Trans. Knowledge and Data Engineering, 16(7):843–857, 2004.
16. F. Zhao, C. Li, and C. F. Liu. A cloud computing security solution based on fully homomor-
phic encryption. in Proc. 16th Int’l Conf. on Advanced Communication Technology, 2014.
17. R. Zhou and K. Hwang. PowerTrust: A Robust and Scalable Reputation System for Trusted
Peer-to-Peer Computing. IEEE Trans. Parallel and Distributed Systems, 18(4):460–473,
2007.
18. Y. Zhu and X. Li. Privacy-preserving k-means clustering with local synchronization in peer-
to-peer networks. Peer-to-Peer Networking and Applications, 13, pp. 2272–2284 (2020).
A Paillier Cryptosystem
To make this paper self-contained, we give a formal definition of Paillier cryptosys-
tem which plays a crucial role in the proposed method.
A.1 Euler’s Theorem
We begin with an important theorem in the number theory, which is known as the
Euler’s theorem.
Euler’s Theorem For any mutually prime positive integers n and a, it holds
aϕ(n)
≡ 1 (mod n)
where ϕ(n) is the Euler’s totient function which returns the number of integers in
{1, 2, . . . , n} which are mutually prime to n.
As an extension of the Euler’s totient function, Paillier cryptosystem uses a
function λ(n) satisfying aλ(n) ≡ 1 (mod n) for any mutually prime integers n and
a. By the Carmichael’s theorem, function λ(n) is represented as
λ(
∏
i
pei
i ) = lcmi(λ(pei−1
i ))
by using the prime factorization of n =
∏
i pei
i , where lcmi denotes the least common
multiple for all i (note that lcmi(pei
i ) = n holds by definition) and each λ(pe) is
defined so that when p = 2,
λ(2e
) =
1 if e = 1
2 if e = 2
2e−2 if e ≥ 3
16
17. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
and for odd prime p,
λ(pe
) = pe−1
(p − 1).
In particular, since n =
∏
i pi implies
λ(n2
) = lcmi(λ(p2
i )) = lcmi(pi × (pi − 1))
=
∏
i
pi × lcmi(pi − 1) = nλ(n),
it holds
aλ(n2)
≡ anλ(n)
≡ 1 (mod n2
) (1)
where the last equation is used to certify the correctness of the decryption in Paillier
cryptosystem.
A.2 Encryption/Decryption
Paillier cryptosystem is a public key cryptosystem. Secret key, which is used for
the decryption, is a pair of sufficiently large prime numbers (p, q), and public
key (g, n), which is used for the encryption, is generated as n := p × q and g :=
(kn + 1) mod n2, where k is a random number drawn from Zn. Given a public key
(g, n), the ciphertext c of a message m satisfying 0 ≤ m < n is calculated as
c := gm
· rn
mod n2
,
where r is a random number in Zn which is independently selected for every time
of the encryption. On the other hand, the decryption of a given ciphertext c is
conducted as:
m :=
L(cλ mod n2)
L(gλ mod n2)
mod n
where L(u) = u−1
n and λ is a number defined as
λ = lcm(p − 1, q − 1).
Recall that by the Carmichael’s theorem, aλ ≡ 1 (mod n) holds for any mutually
prime integers a and n, and since c and g are residuals of a division by n2, a and
n are certainly mutually prime. The decryption of c uses λ which is calculated
from the secret key (p, q), but it is secured by the fact that the factorization of n
is computationally hard. Now let us verify whether the above procedure certainly
decrypts c to plaintext m. At first, cλ is calculated as
cλ
= (gm
· rn
)λ
mod n2
⇐ Def. of c
= gmλ
rnλ
mod n2
= gmλ
mod n2
⇐ Eq. (1)
= (1 + kn)mλ
mod n2
⇐ Def. of g
= 1 + mλkn mod n2
,
17
18. International Journal of Computer Networks & Communications (IJCNC) Vol.13, No.6, 2021
where the last equality is derived from (1+an)k ≡ 1+ank (mod n2), which can be
proven by using the binomial theorem. Note that the above operation eliminates
the random number r used in the encryption. Similarly, gλ can be calculated as
gλ
= (1 + kn)λ
mod n2
= 1 + λkn mod n2
.
Thus, by applying function L to them, we have
L(cλ mod n2)
L(gλ mod n2)
mod n =
mλk
λk
mod n = m mod n,
which certainly realizes the decryption.
A.3 Additive Homomorphism
Pailier cryptosystem satisfies the additive homomorphism in the sense that the
decryption of the product of two ciphertexts equals to the sum of plaintexts. Let
c1 and c2 be ciphertexts of messages m1 and m2, respectively, and let c := c1 ×
c2 mod n2. Then, since
cλ
= (c1 · c2)λ
mod n2
= (gm1
· rn
1 · gm2
· rn
2 )λ
mod n2
= g(m1+m2)λ
mod n2
= (1 + kn)(m1+m2)λ
mod n2
= 1 + (m1 + m2)λkn mod n2
,
the additive homomorphism certainly follows. It is also known that Pailier cryp-
tosystem satisfies a property such that decrypting the ciphertext of m1 to the power
of m2 yields m1 × m2. Let c1 be the ciphertext of m1 snd c := cm2
1 mod n2. Then,
since
cλ
= (gm1
· rn
1 )λm2
mod n2
= g(m1·m2)λ
mod n2
= (1 + kn)(m1·m2)λ
mod n2
= 1 + (m1 · m2)λkn mod n2
,
this property certainly follows.
18