In MANETs the cooperation between nodes of the network is more important for data transmission to occur in a efficient manner. But, it is not true that all nodes of the network actively participate in data transmission process without affecting network performance. The nodes with selfish behavior reject to cooperate with other neighbor nodes of the network for data transmission activity. Selfish nodes lower the performance of the network by causing data loss or they induce wrong data in the network. The existing local watchdog mechanism is used to identify such nodes, but it is not a good mechanism because it originates wrong positives and wrong negatives. So, in this paper we are introducing a watchman with cooperative characteristic to mark greedy nodes and distribute the same information to other neighbor nodes. With this the energy consumption is saved and the selfish nodes are identified earlier and accurately
Now a day the technology is improving day by day. The wired network has been changed to wireless network. There are many advantages of wireless network over wired network. One of the main advantage is we can walk around freely in a network area and accesses internet. Security is one of the challenging issues. Intrusion Detection System is one of the systematic ways to detect malicious node in a mobile ad hoc network MANET and it is driven by battery power. This paper gives a survey on various intrusion detection systems in MANET. Praveen Mourya | Prof. Avinash Sharma ""Review on Intrusion Detection in MANETs"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29970.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/29970/review-on-intrusion-detection-in-manets/praveen-mourya
A collaborative contact based watchdog for detecting selfish nodes in coopera...eSAT Journals
Abstract Mobile Ad-hoc Networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as Delay Tolerant Networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, this paper propose CoCoWa (Collaborative Contact-based Watchdog) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes. Keywords: Opportunistic and Delay Tolerant Networks, Performance Evaluation, Selfish Nodes Wireless networks, MANETs.
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.
Detecting Misbehaving and Selfish Nodes in the Network using Watchdog MechanismINFOGAIN PUBLICATION
The nodes in a wireless network may misbehave at times. This misbehavior needs to be monitored in order to avoid sudden failure of network. The watch dog mechanism has been sufficiently studied to address the issue of malice node detection, in Mobile Adhoc Networks (MANETs). A Collaborative Contact based Watchdog (CoCoWa) is collaborated with information diffusion in the proposed work. This combination strategy analyses all the nodes in a network and provides the information update regarding the selfishness of the specific nodes to other nodes and routing protocols to enable performance oriented transmission. Once the selfish node is detected by the watch dog, it is marked as selfishness positive node else the node is marked as negative selfish node. For enabling this fool proof approach, true neighbors, fake neighbors, their probability of relationships with each other is analyzed. The evaluation of the viability of the proposed work is made in terms of detection efficiency, detection accuracy of both malicious and selfish nodes. Apart from these, the strategy is proved to be simple yet effective.
Study on security and quality of service implementations in p2 p overlay netw...eSAT Publishing House
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
Privacy Preserving and Detection Techniques for Malicious Packet Dropping in ...IRJET Journal
This document discusses techniques for detecting malicious packet dropping in wireless ad hoc networks. It begins with an introduction to wireless ad hoc networks and the security issues they face, such as packet dropping attacks. It then reviews existing literature on detecting such attacks using techniques like reputation systems. The document proposes a new detection mechanism that calculates the auto-correlation function of packet loss bitmaps to identify correlations between lost packets and determine if packet dropping is intentional. It describes the key phases of this approach, including key generation, auditing suspected nodes, and detecting malicious nodes. Finally, it discusses using randomized routing to mitigate the effects of detected packet dropping attacks.
A Paper on Web Data Segmentation for Terrorism Detection using Named Entity R...IRJET Journal
This paper proposes a system to detect web pages and tweets that may promote terrorism using data mining and machine learning techniques. It involves extracting text data from web pages using DOM trees, segmenting tweets and web data using named entity recognition, clustering segmented data using k-means, and applying techniques like SIFT and pattern matching to detect potentially terrorist content. The aim is to automatically flag such web pages and tweets for human review to help curb the spread of terrorism online.
Behavioral Model to Detect Anomalous Attacks in Packet TransmissionIOSR Journals
This document summarizes a proposed behavioral model to detect anomalous attacks in packet transmission in wireless networks. The model aims to identify packet droppers and modifiers by having nodes monitor their neighbors' forwarding behaviors over time. A tree-based routing structure is used, where each packet is marked as it travels toward the sink node. The marks provide information to help the sink node determine which nodes are misbehaving. The proposed scheme aims to gradually identify bad nodes through statistical analysis of their behaviors across different network topologies over time, with low false positives. It aims to catch both packet droppers and modifiers within a single detection module.
Now a day the technology is improving day by day. The wired network has been changed to wireless network. There are many advantages of wireless network over wired network. One of the main advantage is we can walk around freely in a network area and accesses internet. Security is one of the challenging issues. Intrusion Detection System is one of the systematic ways to detect malicious node in a mobile ad hoc network MANET and it is driven by battery power. This paper gives a survey on various intrusion detection systems in MANET. Praveen Mourya | Prof. Avinash Sharma ""Review on Intrusion Detection in MANETs"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020, URL: https://www.ijtsrd.com/papers/ijtsrd29970.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/29970/review-on-intrusion-detection-in-manets/praveen-mourya
A collaborative contact based watchdog for detecting selfish nodes in coopera...eSAT Journals
Abstract Mobile Ad-hoc Networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is specially important on networks with sporadic contacts, such as Delay Tolerant Networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, this paper propose CoCoWa (Collaborative Contact-based Watchdog) as a collaborative approach based on the diffusion of local selfish nodes awareness when a contact occurs, so that information about selfish nodes is quickly propagated. As shown in the paper, this collaborative approach reduces the time and increases the precision when detecting selfish nodes. Keywords: Opportunistic and Delay Tolerant Networks, Performance Evaluation, Selfish Nodes Wireless networks, MANETs.
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.
Detecting Misbehaving and Selfish Nodes in the Network using Watchdog MechanismINFOGAIN PUBLICATION
The nodes in a wireless network may misbehave at times. This misbehavior needs to be monitored in order to avoid sudden failure of network. The watch dog mechanism has been sufficiently studied to address the issue of malice node detection, in Mobile Adhoc Networks (MANETs). A Collaborative Contact based Watchdog (CoCoWa) is collaborated with information diffusion in the proposed work. This combination strategy analyses all the nodes in a network and provides the information update regarding the selfishness of the specific nodes to other nodes and routing protocols to enable performance oriented transmission. Once the selfish node is detected by the watch dog, it is marked as selfishness positive node else the node is marked as negative selfish node. For enabling this fool proof approach, true neighbors, fake neighbors, their probability of relationships with each other is analyzed. The evaluation of the viability of the proposed work is made in terms of detection efficiency, detection accuracy of both malicious and selfish nodes. Apart from these, the strategy is proved to be simple yet effective.
Study on security and quality of service implementations in p2 p overlay netw...eSAT Publishing House
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
Privacy Preserving and Detection Techniques for Malicious Packet Dropping in ...IRJET Journal
This document discusses techniques for detecting malicious packet dropping in wireless ad hoc networks. It begins with an introduction to wireless ad hoc networks and the security issues they face, such as packet dropping attacks. It then reviews existing literature on detecting such attacks using techniques like reputation systems. The document proposes a new detection mechanism that calculates the auto-correlation function of packet loss bitmaps to identify correlations between lost packets and determine if packet dropping is intentional. It describes the key phases of this approach, including key generation, auditing suspected nodes, and detecting malicious nodes. Finally, it discusses using randomized routing to mitigate the effects of detected packet dropping attacks.
A Paper on Web Data Segmentation for Terrorism Detection using Named Entity R...IRJET Journal
This paper proposes a system to detect web pages and tweets that may promote terrorism using data mining and machine learning techniques. It involves extracting text data from web pages using DOM trees, segmenting tweets and web data using named entity recognition, clustering segmented data using k-means, and applying techniques like SIFT and pattern matching to detect potentially terrorist content. The aim is to automatically flag such web pages and tweets for human review to help curb the spread of terrorism online.
Behavioral Model to Detect Anomalous Attacks in Packet TransmissionIOSR Journals
This document summarizes a proposed behavioral model to detect anomalous attacks in packet transmission in wireless networks. The model aims to identify packet droppers and modifiers by having nodes monitor their neighbors' forwarding behaviors over time. A tree-based routing structure is used, where each packet is marked as it travels toward the sink node. The marks provide information to help the sink node determine which nodes are misbehaving. The proposed scheme aims to gradually identify bad nodes through statistical analysis of their behaviors across different network topologies over time, with low false positives. It aims to catch both packet droppers and modifiers within a single detection module.
Multiple intrusion detection in RPL based networks IJECEIAES
Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.
This document compares the k-means data mining and outlier detection approaches for network-based intrusion detection. It analyzes four datasets capturing network traffic using both approaches. The k-means approach clusters traffic into normal and abnormal flows, while outlier detection calculates an outlier score for each flow. The document finds that k-means was more accurate and precise, with a better classification rate than outlier detection. It requires less computer resources than outlier detection. This comparison of the approaches can help network administrators choose the best intrusion detection method.
Artificial Neural Content Techniques for Enhanced Intrusion Detection and Pre...AM Publications
This paper presents a novel approach for detecting network intrusions based on a competitive training neural
network. In the paper, the performance of this approach is compared to that of the self-organizing map (SOM), which is a
popular unsupervised training algorithm used in intrusion detection. While obtaining a similarly accurate detection rate as
the SOM does, the proposed approach uses only one forth of the computation times of the SOM. Furthermore, the
clustering result of this method is independent of the number of the initial neurons. This approach also exhibits the ability
to detect the known and unknown network attacks. The experimental results obtained by applying this approach to the
KDD-99 data set demonstrate that the proposed approach performs exceptionally in terms of both accuracy and
computation time.
Identifying Malicious Data in Social MediaIRJET Journal
This document discusses two approaches for identifying malicious data in social media: Shannon entropy and power law distribution. The Shannon entropy approach calculates the entropy of features like source/destination IP addresses and port numbers to detect anomalous network traffic patterns. The power law distribution approach models malware propagation across networks and finds that malware distribution transitions from exponential to power law over time. Experimental results on social media datasets found the Shannon entropy approach could detect malware based on the number of applications installed, while power law distribution identified good and malicious files shared between users. Both techniques aim to improve detection of malicious content shared over social networks.
This document discusses techniques for detecting fake news. It begins with an introduction to the problem of fake news and how it spreads on social media. It then reviews different machine learning techniques that have been used for fake news detection, including naïve bayes, decision trees, random forests, K-nearest neighbors, and LSTM. The document also categorizes different types of fake news and surveys related literature applying machine learning to fake news detection. It concludes that detecting fake news is still an ongoing challenge and more work is needed with improved datasets and models.
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.
IRJET - Twitter Spam Detection using CobwebIRJET Journal
This document discusses using Cobweb clustering and Gradient Boosting techniques to detect spam on Twitter. Cobweb clustering creates a classification tree to predict attributes of new objects by summarizing the attribute distributions of existing nodes. Gradient Boosting is an ensemble method that uses multiple weak learners (decision trees) to create a stronger predictive model. The paper aims to combine these techniques to create an enhanced spam detection system. It also reviews several existing approaches for Twitter spam detection using techniques like Hidden Markov Models, Random Forests, and asynchronous link-based algorithms.
Security Measure to Detect and Avoid Flooding Attacks using Multi-Agent Syste...IJECEIAES
The document proposes a technique to detect flooding attacks in MANETs using a multi-agent system. It begins by introducing MANETs and some of their vulnerabilities like flooding attacks. It then discusses using a multi-agent approach to both detect flooding attacks and maintain network resilience by identifying malicious nodes and using alternative routes. The paper presents an algorithm to optimally determine the number of agents to launch, detect flooding in message buffers, and avoid attacks by blocking malicious nodes and removing affected routes. Simulation results show the approach improves throughput, packet delivery ratio, and reduces end-to-end delay and packet drops compared to AODV.
Detecting root of the rumor in social network using GSSSIRJET Journal
1) The document proposes a method to detect the root of rumors spreading in social networks using monitor nodes and the Greedy Source Set Size algorithm.
2) Monitor nodes record and report data to identify rumors and their sources based on which nodes received the information.
3) The GSSS algorithm aims to find the exact solution and improve efficiency for identifying rumor sources.
4) Three methods are used to identify the rumor root: identification method, reverse dissemination method, and microscopic rumor spreading model based on maximum likelihood.
This document summarizes a research paper that proposes a new security algorithm called a modified cooperative bait detection scheme to detect black hole attacks in the Dynamic Source Routing (DSR) protocol for mobile ad hoc networks. The proposed approach involves three steps: 1) initial setup to detect potential malicious nodes, 2) attack identification using reverse tracing to find harmful and non-harmful nodes in the transmission path, and 3) a reactive protection step to locate malicious locations based on energy cost. Experimental results showed that the proposed method performed better than existing approaches in terms of detection accuracy, misclassification rate, detection time, and other metrics.
Network Security: Experiment of Network Health Analysis At An ISPCSCJournals
This paper presents the findings of an analysis performed at an internet service provider. Based on netflow data collected and analyzed using nfdump, it helped assess how healthy is the network of an Internet Service Providers (ISP). The findings have been instrumental in reflection about reshaping the network architecture. And they have also demonstrated the need for consistent monitoring system.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
CONTROLLING IP FALSIFYING USING REALISTIC SIMULATIONIJNSA Journal
This document discusses a proposal to develop a new distributed Internet simulator to study large-scale network events like distributed denial-of-service (DDoS) attacks and worm propagation. Existing network simulators have limited scalability and lack realistic Internet models. The proposed simulator would have a built-in Internet topology model and customizeable modules to simulate specific events while cutting down on unnecessary details. It aims to make large-scale network simulation more accessible to researchers and improve the realism of simulations compared to simplified models currently used. The simulator could help study defenses against problems like IP spoofing, DDoS attacks, and worms.
IRJET- Attack Detection Strategies in Wireless Sensor NetworkIRJET Journal
The document discusses various attack detection strategies in wireless sensor networks, including centralized techniques like straightforward detection, set operations, and cluster-based approaches as well as distributed techniques like content-based and attribute-based filtering. It compares the techniques on factors like the type of attack detected and their merits and demerits. The conclusion calls for improved validation mechanisms to authenticate users and reduce deceptions like clone attacks on social media networks.
This paper introduces co-operative caching
policies for reducing electronic content provisioning cost in
Social Wireless Networks (SWNET). SWNET are formed by
mobile devices such as laptops, modern cell phones etc. sharing
common electronic contents, data and actually gathering in
public places like college campus, mall etc. Electronic object
caching in such SWNET are shown to be able to minimize the
content provisioning cost which mainly depend on service and
pricing dependencies between various stakeholders including
content provider(CP), network service provider, end
consumer(EC). This paper introduces practical network service
and pricing model which are used for creating two object
caching strategies for minimizing provisioning cost in networks
which are homogeneous and heterogeneous object demand. The
paper develops analytical and simulation design for analyzing
the proposed caching strategies in the presence of selfish user
that deviates from networks-wide cost-optimal policies.
A adaptive neighbor analysis approach to detect cooperative selfish node in m...Jyoti Parashar
Mobile network is a set of wireless device called wireless nodes(mobile, Laptop) which are dynamically connect and transfer the information. In MANET nodes can be source, destination and intermediate node of data transmission.
IRJET- Monitoring Suspicious Discussions on Online Forums using Data MiningIRJET Journal
1) The document discusses monitoring suspicious discussions on online forums using data mining techniques. It aims to reduce suspicious activity, notify administrators of malicious users, and identify and convert negative words.
2) It proposes collecting data from forums, analyzing it using naive Bayes classification in Python to identify positive and negative sentiment, and replacing negative words with asterisks while notifying the administrator.
3) The method architecturally involves users logging into a forum, discussions being monitored for suspicious words, and administrators getting notified if detected along with users getting warned. It concludes the objectives of monitoring forums are satisfied.
A COMPARATIVE STUDY OF SOCIAL NETWORKING APPROACHES IN IDENTIFYING THE COVERT...ijwscjournal
This document summarizes and compares different approaches to analyzing covert networks through social network analysis and criminal network analysis. It categorizes approaches into areas like link analysis, node discovery, dynamic network analysis, key player identification, and applying these techniques to homeland security issues. It provides examples of studies that use techniques like link analysis to identify criminal associations, node discovery to find covert nodes, and dynamic network analysis tools to model network changes over time. The goal is to identify methodologies for discovering covert nodes and relationships within terrorist and criminal networks.
Detection of Node Activity and Selfish & Malicious Behavioral Patterns using ...ijcnes
Mobile ad-hoc networks(MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is especially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, We apply chord algorithm to identify behavior pattern of one shelf by two neighborhood nodes and themselves. Servers will finally categories nature of node.
A Survey of Techniques Used To Detect Selfish Nodes in MANETijsrd.com
This document summarizes various techniques that have been used to detect selfish nodes in mobile ad hoc networks (MANETs). It begins with an introduction to MANETs and the problem of selfish nodes. It then describes several common approaches for detecting selfish nodes, including reputation-based schemes, credit-based schemes, and acknowledgement-based schemes. Specific techniques are discussed like watchdog, pathrater, CONFIDANT, CORE, OCEAN, 2ACK scheme, SORI, LARS, and others. Their advantages and disadvantages are summarized. Finally, the document proposes a combined approach using collaborative watchdog and credit risk to more quickly detect selfish nodes in a decentralized way while reducing overhead.
Network Security Enhancement in WSN by Detecting Misbehavioural Activity as C...ijtsrd
This system proposes a centralized system for replica identification. The network is divided into segments and an inspection node is chosen for each segment. Inspection node identifies a clone node by checking the nodes ID and cryptographic key. In this process, Chord algorithm is used to detect the clone node, every node is assigned with random key, before it transmits the data it has to give its key which would be verified by the witness node. If same key is given by another node then the witness node identifies the cloned node. Here every node only needs to know the neighbor list containing all neighbor IDs and its location. In this scheme, Energy Efficient Clustering Protocol EECP protocol is used to implement different energy saving methods. Dr. B. R. Tapas Bapu | Hemavathi S U | Poonkuzhali K | Sweety J "Network Security Enhancement in WSN by Detecting Misbehavioural Activity as Copy Cat Nodes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31257.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31257/network-security-enhancement-in-wsn-by-detecting-misbehavioural-activity-as-copy-cat-nodes/dr-b-r-tapas-bapu
Proposed Agent Based Black hole Node Detection Algorithm for Ad-Hoc Wireless...ijcsa
A Mobile ad-hoc network (MANET) is a latest and eme
rging Research topic among researchers. The
reason behind the popularity of MANET is flexibilit
y and independence of network infrastructure. MANET
has some unique characteristic like dynamic network
topology, limited power and limited bandwidth for
communication. MANET has more challenge compare to
any other conventional network. However the
dynamical network topology of MANETs, infrastructur
e-less property and lack of certificate authority m
ake
the security problems of MANETs need to pay more at
tention. This paper represents review of layer wise
security attacks. It also discussed the issues and
challenges of mobile ad hoc network. On the importa
nce of
security issues, this paper proposed intrusion dete
ction framework for detecting network layer threats
such
as black hole attack.
Multiple intrusion detection in RPL based networks IJECEIAES
Routing Protocol for Low Power and Lossy Networks based networks consists of large number of tiny sensor nodes with limited resources. These nodes are directly connected to the Internet through the border router. Hence these nodes are susceptible to different types of attacks. The possible attacks are rank attack, selective forwarding, worm hole and Denial of service attack. These attacks can be effectively identified by intrusion detection system model. The paper focuses on identification of multiple intrusions by considering the network size as 10, 40 and 100 nodes and adding 10%, 20% and 30% of malicious nodes to the considered network. Experiments are simulated using Cooja simulator on Contiki operating system. Behavior of the network is observed based on the percentage of inconsistency achieved, energy consumption, accuracy and false positive rate. Experimental results show that multiple intrusions can be detected effectively by machine learning techniques.
This document compares the k-means data mining and outlier detection approaches for network-based intrusion detection. It analyzes four datasets capturing network traffic using both approaches. The k-means approach clusters traffic into normal and abnormal flows, while outlier detection calculates an outlier score for each flow. The document finds that k-means was more accurate and precise, with a better classification rate than outlier detection. It requires less computer resources than outlier detection. This comparison of the approaches can help network administrators choose the best intrusion detection method.
Artificial Neural Content Techniques for Enhanced Intrusion Detection and Pre...AM Publications
This paper presents a novel approach for detecting network intrusions based on a competitive training neural
network. In the paper, the performance of this approach is compared to that of the self-organizing map (SOM), which is a
popular unsupervised training algorithm used in intrusion detection. While obtaining a similarly accurate detection rate as
the SOM does, the proposed approach uses only one forth of the computation times of the SOM. Furthermore, the
clustering result of this method is independent of the number of the initial neurons. This approach also exhibits the ability
to detect the known and unknown network attacks. The experimental results obtained by applying this approach to the
KDD-99 data set demonstrate that the proposed approach performs exceptionally in terms of both accuracy and
computation time.
Identifying Malicious Data in Social MediaIRJET Journal
This document discusses two approaches for identifying malicious data in social media: Shannon entropy and power law distribution. The Shannon entropy approach calculates the entropy of features like source/destination IP addresses and port numbers to detect anomalous network traffic patterns. The power law distribution approach models malware propagation across networks and finds that malware distribution transitions from exponential to power law over time. Experimental results on social media datasets found the Shannon entropy approach could detect malware based on the number of applications installed, while power law distribution identified good and malicious files shared between users. Both techniques aim to improve detection of malicious content shared over social networks.
This document discusses techniques for detecting fake news. It begins with an introduction to the problem of fake news and how it spreads on social media. It then reviews different machine learning techniques that have been used for fake news detection, including naïve bayes, decision trees, random forests, K-nearest neighbors, and LSTM. The document also categorizes different types of fake news and surveys related literature applying machine learning to fake news detection. It concludes that detecting fake news is still an ongoing challenge and more work is needed with improved datasets and models.
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.
IRJET - Twitter Spam Detection using CobwebIRJET Journal
This document discusses using Cobweb clustering and Gradient Boosting techniques to detect spam on Twitter. Cobweb clustering creates a classification tree to predict attributes of new objects by summarizing the attribute distributions of existing nodes. Gradient Boosting is an ensemble method that uses multiple weak learners (decision trees) to create a stronger predictive model. The paper aims to combine these techniques to create an enhanced spam detection system. It also reviews several existing approaches for Twitter spam detection using techniques like Hidden Markov Models, Random Forests, and asynchronous link-based algorithms.
Security Measure to Detect and Avoid Flooding Attacks using Multi-Agent Syste...IJECEIAES
The document proposes a technique to detect flooding attacks in MANETs using a multi-agent system. It begins by introducing MANETs and some of their vulnerabilities like flooding attacks. It then discusses using a multi-agent approach to both detect flooding attacks and maintain network resilience by identifying malicious nodes and using alternative routes. The paper presents an algorithm to optimally determine the number of agents to launch, detect flooding in message buffers, and avoid attacks by blocking malicious nodes and removing affected routes. Simulation results show the approach improves throughput, packet delivery ratio, and reduces end-to-end delay and packet drops compared to AODV.
Detecting root of the rumor in social network using GSSSIRJET Journal
1) The document proposes a method to detect the root of rumors spreading in social networks using monitor nodes and the Greedy Source Set Size algorithm.
2) Monitor nodes record and report data to identify rumors and their sources based on which nodes received the information.
3) The GSSS algorithm aims to find the exact solution and improve efficiency for identifying rumor sources.
4) Three methods are used to identify the rumor root: identification method, reverse dissemination method, and microscopic rumor spreading model based on maximum likelihood.
This document summarizes a research paper that proposes a new security algorithm called a modified cooperative bait detection scheme to detect black hole attacks in the Dynamic Source Routing (DSR) protocol for mobile ad hoc networks. The proposed approach involves three steps: 1) initial setup to detect potential malicious nodes, 2) attack identification using reverse tracing to find harmful and non-harmful nodes in the transmission path, and 3) a reactive protection step to locate malicious locations based on energy cost. Experimental results showed that the proposed method performed better than existing approaches in terms of detection accuracy, misclassification rate, detection time, and other metrics.
Network Security: Experiment of Network Health Analysis At An ISPCSCJournals
This paper presents the findings of an analysis performed at an internet service provider. Based on netflow data collected and analyzed using nfdump, it helped assess how healthy is the network of an Internet Service Providers (ISP). The findings have been instrumental in reflection about reshaping the network architecture. And they have also demonstrated the need for consistent monitoring system.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
CONTROLLING IP FALSIFYING USING REALISTIC SIMULATIONIJNSA Journal
This document discusses a proposal to develop a new distributed Internet simulator to study large-scale network events like distributed denial-of-service (DDoS) attacks and worm propagation. Existing network simulators have limited scalability and lack realistic Internet models. The proposed simulator would have a built-in Internet topology model and customizeable modules to simulate specific events while cutting down on unnecessary details. It aims to make large-scale network simulation more accessible to researchers and improve the realism of simulations compared to simplified models currently used. The simulator could help study defenses against problems like IP spoofing, DDoS attacks, and worms.
IRJET- Attack Detection Strategies in Wireless Sensor NetworkIRJET Journal
The document discusses various attack detection strategies in wireless sensor networks, including centralized techniques like straightforward detection, set operations, and cluster-based approaches as well as distributed techniques like content-based and attribute-based filtering. It compares the techniques on factors like the type of attack detected and their merits and demerits. The conclusion calls for improved validation mechanisms to authenticate users and reduce deceptions like clone attacks on social media networks.
This paper introduces co-operative caching
policies for reducing electronic content provisioning cost in
Social Wireless Networks (SWNET). SWNET are formed by
mobile devices such as laptops, modern cell phones etc. sharing
common electronic contents, data and actually gathering in
public places like college campus, mall etc. Electronic object
caching in such SWNET are shown to be able to minimize the
content provisioning cost which mainly depend on service and
pricing dependencies between various stakeholders including
content provider(CP), network service provider, end
consumer(EC). This paper introduces practical network service
and pricing model which are used for creating two object
caching strategies for minimizing provisioning cost in networks
which are homogeneous and heterogeneous object demand. The
paper develops analytical and simulation design for analyzing
the proposed caching strategies in the presence of selfish user
that deviates from networks-wide cost-optimal policies.
A adaptive neighbor analysis approach to detect cooperative selfish node in m...Jyoti Parashar
Mobile network is a set of wireless device called wireless nodes(mobile, Laptop) which are dynamically connect and transfer the information. In MANET nodes can be source, destination and intermediate node of data transmission.
IRJET- Monitoring Suspicious Discussions on Online Forums using Data MiningIRJET Journal
1) The document discusses monitoring suspicious discussions on online forums using data mining techniques. It aims to reduce suspicious activity, notify administrators of malicious users, and identify and convert negative words.
2) It proposes collecting data from forums, analyzing it using naive Bayes classification in Python to identify positive and negative sentiment, and replacing negative words with asterisks while notifying the administrator.
3) The method architecturally involves users logging into a forum, discussions being monitored for suspicious words, and administrators getting notified if detected along with users getting warned. It concludes the objectives of monitoring forums are satisfied.
A COMPARATIVE STUDY OF SOCIAL NETWORKING APPROACHES IN IDENTIFYING THE COVERT...ijwscjournal
This document summarizes and compares different approaches to analyzing covert networks through social network analysis and criminal network analysis. It categorizes approaches into areas like link analysis, node discovery, dynamic network analysis, key player identification, and applying these techniques to homeland security issues. It provides examples of studies that use techniques like link analysis to identify criminal associations, node discovery to find covert nodes, and dynamic network analysis tools to model network changes over time. The goal is to identify methodologies for discovering covert nodes and relationships within terrorist and criminal networks.
Detection of Node Activity and Selfish & Malicious Behavioral Patterns using ...ijcnes
Mobile ad-hoc networks(MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behaviour. Thus, the overall network performance could be seriously affected. The use of watchdogs is a well-known mechanism to detect selfish nodes. However, the detection process performed by watchdogs can fail, generating false positives and false negatives that can induce to wrong operations. Moreover, relying on local watchdogs alone can lead to poor performance when detecting selfish nodes, in term of precision and speed. This is especially important on networks with sporadic contacts, such as delay tolerant networks (DTNs), where sometimes watchdogs lack of enough time or information to detect the selfish nodes. Thus, We apply chord algorithm to identify behavior pattern of one shelf by two neighborhood nodes and themselves. Servers will finally categories nature of node.
A Survey of Techniques Used To Detect Selfish Nodes in MANETijsrd.com
This document summarizes various techniques that have been used to detect selfish nodes in mobile ad hoc networks (MANETs). It begins with an introduction to MANETs and the problem of selfish nodes. It then describes several common approaches for detecting selfish nodes, including reputation-based schemes, credit-based schemes, and acknowledgement-based schemes. Specific techniques are discussed like watchdog, pathrater, CONFIDANT, CORE, OCEAN, 2ACK scheme, SORI, LARS, and others. Their advantages and disadvantages are summarized. Finally, the document proposes a combined approach using collaborative watchdog and credit risk to more quickly detect selfish nodes in a decentralized way while reducing overhead.
Network Security Enhancement in WSN by Detecting Misbehavioural Activity as C...ijtsrd
This system proposes a centralized system for replica identification. The network is divided into segments and an inspection node is chosen for each segment. Inspection node identifies a clone node by checking the nodes ID and cryptographic key. In this process, Chord algorithm is used to detect the clone node, every node is assigned with random key, before it transmits the data it has to give its key which would be verified by the witness node. If same key is given by another node then the witness node identifies the cloned node. Here every node only needs to know the neighbor list containing all neighbor IDs and its location. In this scheme, Energy Efficient Clustering Protocol EECP protocol is used to implement different energy saving methods. Dr. B. R. Tapas Bapu | Hemavathi S U | Poonkuzhali K | Sweety J "Network Security Enhancement in WSN by Detecting Misbehavioural Activity as Copy Cat Nodes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31257.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/31257/network-security-enhancement-in-wsn-by-detecting-misbehavioural-activity-as-copy-cat-nodes/dr-b-r-tapas-bapu
Proposed Agent Based Black hole Node Detection Algorithm for Ad-Hoc Wireless...ijcsa
A Mobile ad-hoc network (MANET) is a latest and eme
rging Research topic among researchers. The
reason behind the popularity of MANET is flexibilit
y and independence of network infrastructure. MANET
has some unique characteristic like dynamic network
topology, limited power and limited bandwidth for
communication. MANET has more challenge compare to
any other conventional network. However the
dynamical network topology of MANETs, infrastructur
e-less property and lack of certificate authority m
ake
the security problems of MANETs need to pay more at
tention. This paper represents review of layer wise
security attacks. It also discussed the issues and
challenges of mobile ad hoc network. On the importa
nce of
security issues, this paper proposed intrusion dete
ction framework for detecting network layer threats
such
as black hole attack.
The document proposes a behavioral model called PFMDA to detect anomalous packet dropping and modification attacks in wireless ad hoc networks. The PFMDA scheme establishes a routing tree with the sink node at the root. As data packets are transmitted along the tree, each sender or forwarder adds a small number of "packet marks" to the packet. This allows the sink to determine the dropping ratio for each node and identify nodes that are definitely dropping/modifying packets or are suspicious of such behavior. The scheme uses node categorization and heuristic ranking algorithms to gradually identify misbehaving nodes with few false positives. The goal is to detect packet droppers and modifiers within the network.
Wireless Sensor Networks (WSNs) are often deployed in unfavourable situations where an assailant can physically capture some of the nodes, first can reprogram, and then, can replicate them in a large number of clones, easily taking control over the network. This replication node is also called as Clone node. The clone node or replicated node behave as a genuine node. It can damage the network. In node replication attack detecting the clone node important issue in Wireless Sensor Networks. A few distributed solutions have been recently proposed, but they are not satisfactory. First, they are intensity and memory demanding: A serious drawback for any protocol to be used in the WSN- resource constrained environment. In this project first investigate the selection criteria of clone detection schemes with regard to device types, detection methodologies, deployment strategies, and detection ranges. Further, they are vulnerable to the specific assailant models introduced in this paper. In this scenario, a particularly dangerous attack is the replica attack, in which the assailant takes the secret keying materials from a compromised node, generates a large number of assailant-controlled replicas that share the node’s keying materials and ID, and then spreads these replicas throughout the network. With a single captured node, the assailant can create as many replica nodes as he has the hardware to generate.. The replica nodes are controlled by the assailant, but have keying materials that allow them to seem like authorized participants in the network. Our implementation specifies, user will specify its ID, which means client id, secret key will be create, and then include the port number. The witness node will verify the internally bounded user Id and secret key. The witness node means original node. If the verification is success, the information collecting to the packets that packets are send to the destination.
Energy Efficinet Intrusion Detection System in mobile ad-hoc networksIJARIIE JOURNAL
This document summarizes a proposed energy efficient intrusion detection system for mobile ad-hoc networks. It begins with an introduction to intrusion detection systems and mobile ad-hoc networks. It then discusses related work on intrusion detection in mobile ad-hoc networks. The proposed system uses an "impact factor" calculation to select cluster heads in an energy-efficient manner while preventing selfish behavior. Cluster heads run the intrusion detection system using a watchdog method to detect misbehaving nodes. Simulation results show that forming clusters reduces energy consumption compared to all nodes running intrusion detection independently.
IRJET- Detection and Prevention Methodology for Dos Attack in Mobile Ad-Hoc N...IRJET Journal
1) The document discusses detection and prevention of denial of service (DoS) attacks in mobile ad-hoc networks.
2) It focuses on identifying malicious nodes that conduct traffic jamming attacks by disrupting communication.
3) The proposed approach detects malicious nodes using a reliability value determined by broadcast reliability packets, where nodes that don't respond in a set time have their reliability value decreased until it reaches below zero, identifying them as malicious.
https://jst.org.in/index.html
Our journal has digital transformation, effective management strategies are crucial. Our pages unfold discussions on navigating the complexities of modern business landscapes, strategic decision-making, and adaptive leadership—essential elements for success in the 21st century.
New Similarity Index for Finding Followers in Leaders Based Community DetectionIRJET Journal
This document presents a new similarity index method for improving the accuracy of leader-based community detection in large networks. Leader-based community detection identifies influential leader nodes and assigns other nodes as followers based on their similarity to the leaders. The existing method's accuracy decreases as the network size increases. The proposed method modifies the similarity calculation to increase accuracy for networks with more than 2000 nodes. It was tested on synthetic networks generated by the LFR benchmark model and evaluated using normalized mutual information and adjusted rand index, showing accuracy remains high even for large networks.
A Comparative Study for Source Privacy Preserving and Message Authentication ...AM Publications
Source node privacy and message authentication are the most important issues to be addressed in wireless sensor networks. Many schemes have come up to deal with message authentication. However, some of the schemes have stood by with some limitations like lack of scalability and high communication and computational overhead. Later these issues were solved by a polynomial based scheme, but failed to transmit number of messages beyond its threshold. To overcome this limitation an ECC and RSA algorithm has been used. To fix all these issues, a source node privacy based message authentication using Greedy Random walk algorithm has been proposed in this paper. A comparative study is done for the work that is implemented using ns2 and matlab.
A Survey on Data Intrusion schemes used in MANETIRJET Journal
The document discusses data intrusion schemes used in mobile ad hoc networks (MANETs). It reviews common problems with data intrusion in MANETs due to their dynamic architecture and limited resources. Several proposed intrusion detection schemes are described, including distributed and cooperative schemes, specification-based schemes, and the proposed Random Walker Detection method. The proposed method aims to efficiently detect intrusions by deploying detection engines at each node and excluding detection engines from random walkers to reduce detection latency. It is described as working on three network layers and using advanced encryption standards to securely detect and route around malicious nodes.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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This document summarizes a research paper that proposes a new solution to detect and prevent selfish attacks in mobile ad hoc networks (MANETs). The solution uses a watchdog technique to monitor node behavior and a varying threshold-based policy to avoid falsely accusing nodes in dense networks. It describes how the Ad Hoc On-Demand Distance Vector (AODV) routing protocol works in MANETs and related work on detecting and preventing selfish attacks. The proposed technique aims to safely monitor, detect, and isolate misbehaving nodes through dynamic learning without falsely accusing correct nodes.
A Survey on Cloud-Based IP Trace Back FrameworkIRJET Journal
This document summarizes a survey of cloud-based IP traceback frameworks. It proposes a cloud-based traceback architecture with three layers: an intra-AS layer where traceback servers in each Autonomous System (AS) collect and store traffic flow data; a traceback as a service layer where ASes expose their traceback capabilities; and an inter-AS logical links layer to facilitate efficient traceback across ASes. It then focuses on access control to prevent unauthorized users from requesting traceback information. To address this, it proposes a temporal token-based authentication framework called FACT that embeds tokens in traffic flows and delivers them to end hosts to authenticate traceback queries. The framework aims to ensure only actual recipients of packets can initiate traceback for those packets.
AN EFFICIENT KEY AGREEMENT SCHEME FOR WIRELESSSENSOR NETWORKS USING THIRD PAR...ijasuc
This document summarizes a key agreement scheme for wireless sensor networks that uses third party nodes to assist with pair-wise key establishment between sensor nodes. The proposed scheme has several advantages over existing approaches, including high local connectivity between sensor nodes, low memory usage, and resilience against node capture. It utilizes third party nodes, which are additional nodes deployed only to assist with key establishment and do not perform other network functions like sensing or routing. The scheme distributes secret shares to sensor nodes, allows nodes to discover local neighbors, and establishes secure channels in a way that improves performance metrics like connectivity, security, memory efficiency, and computational overhead compared to other key agreement methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IRJET - Security and Privacy by IDS SystemIRJET Journal
This document summarizes a research paper that proposes an intrusion detection system (IDS) to detect spoofing attacks in wireless sensor networks. The IDS monitors node activities and detects if a node is behaving abnormally or attacking the network. If an attack is detected, the IDS sends an alarm message to the affected node to isolate the attacker. The paper simulates this approach using OTCL language in Network Simulator 2 on Linux. The results show the IDS can efficiently detect spoofing attackers in the wireless network.
A New Approach for Improving Performance of Intrusion Detection System over M...IOSR Journals
This document discusses improving the performance of intrusion detection systems (IDS) in mobile ad hoc networks (MANETs). It proposes using an inverted table approach to track communication information and identify attacker nodes through data mining. The key approaches are:
1. Maintaining an inverted table to record network communication information for analysis.
2. Using data mining techniques like anomaly detection to identify attacker nodes based on patterns in the table.
3. Discovering preventative paths that avoid identified attacker nodes to improve network throughput and reduce data loss.
The approaches aim to improve IDS performance challenged by attacks that slow detection in MANETs. The work will be implemented in NS2 and evaluate performance based on throughput and
A Study on Security in Wireless Sensor Networksijtsrd
Wireless Sensor Networks (WSNs) present myriad application opportunities for several applications such as precision agriculture, environmental and habitat monitoring, traffic control, industrial process monitoring and control, home automation and mission-critical surveillance applications such as military surveillance, healthcare (elderly, home monitoring) applications, disaster relief and management, fire detection applications among others. Since WSNs are used in mission-critical tasks, security is an essential requirement. Sensor nodes can easily be compromised by an adversary due to unique constraints inherent in WSNs such as limited sensor node energy, limited computation and communication capabilities and the hostile deployment environments. Shabnam Kumari | Sumit Dalal | Rashmi"A Study on Security in Wireless Sensor Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-4 , June 2018, URL: http://www.ijtsrd.com/papers/ijtsrd12931.pdf http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/12931/a-study-on-security-in-wireless-sensor-networks/shabnam-kumari
Similar to Identifying Selfish Nodes Using Contact Based Watchman (20)
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Software Engineering and Project Management - Software Testing + Agile Method...Prakhyath Rai
Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
Agile Methodology: Before Agile – Waterfall, Agile Development.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
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