The Use of K-mer Minimizers to Identify Bacterium Genomes in High Throughput ...Mackenna Galicia
Bioinformatics combines the elements of biology, computer science, and statistics to work with genome sequencing. My project utilizes a sequence analysis technique, k-mer minimizers, to identify bacterium from a shotgun genomic DNA sample. We used the algorithm Bevel to compare DNA sequences against standardized reference genomes in the PATRIC whole genome bacterial database. Bevel is a sequence similarity tool that uses a minimizer database. Minimizers are representative k-mers, subsequences of length k observed to have the minimum hash value across a genomic region and are therefore unique and comparable to that genomic region. The two databases are queried against each other, resulting in a list of positions where two or more sequences match. I am developing two Python applications that first, process the results of the algorithm and secondly, return a score that enable the ranking of bacterium matches. The higher the score, the better the match between the unknown bacteria and the standardized reference genome. The goal of this experiment is to show that minimizers are a fast mean of characterizing bacterial shotgun assembly contigs.
Using Cisco Network Components to Improve NIDPS Performance csandit
Network Intrusion Detection and Prevention Systems (NIDPSs) are used to detect, prevent and
report evidence of attacks and malicious traffic. Our paper presents a study where we used open
source NIDPS software. We show that NIDPS detection performance can be weak in the face of
high-speed and high-load traffic in terms of missed alerts and missed logs. To counteract this
problem, we have proposed and evaluated a solution that utilizes QoS, queues and parallel
technologies in a multi-layer Cisco Catalyst Switch to increase NIDPSs detection performance.
Our approach designs a novel QoS architecture to organise and improve throughput-forwardplan
traffic in a layer 3 switch in order to improve NIDPS performance.
Outsourced kp abe with chosen ciphertext securitycsandit
Key-Policy Attribute Based Encryption (KP-ABE) has always been criticized for its inefficiency
drawbacks. Based on the cloud computing technology, computation outsourcing is one of the
effective solution to this problem. Some papers have proposed their schemes; however,
adversaries in their attack models were divided into two categories and they are assumed not to
communicate with each other, which is obviously unrealistic. In this paper, we first proved there
exist severe security vulnerabilities in these schemes for such an assumption, and then proposed
a security enhanced Chosen Ciphertext Attack (SE-CCA) model, which eliminates the improper
limitations. By utilizing Proxy Re-Encryption (PRE) and one-time signature technology, we also
constructed a concrete KP-ABE outsourcing scheme (O-KP-ABE) and proved its security under
SE-CCA model. Comparisons with existing schemes show that our constructions have obvious
comprehensive advantages in security and efficiency.
Data mining is the knowledge discovery in databases and the gaol is to extract patterns and knowledge from
large amounts of data. The important term in data mining is text mining. Text mining extracts the quality
information highly from text. Statistical pattern learning is used to high quality information. High –quality in
text mining defines the combinations of relevance, novelty and interestingness. Tasks in text mining are text
categorization, text clustering, entity extraction and sentiment analysis. Applications of natural language
processing and analytical methods are highly preferred to turn
The Use of K-mer Minimizers to Identify Bacterium Genomes in High Throughput ...Mackenna Galicia
Bioinformatics combines the elements of biology, computer science, and statistics to work with genome sequencing. My project utilizes a sequence analysis technique, k-mer minimizers, to identify bacterium from a shotgun genomic DNA sample. We used the algorithm Bevel to compare DNA sequences against standardized reference genomes in the PATRIC whole genome bacterial database. Bevel is a sequence similarity tool that uses a minimizer database. Minimizers are representative k-mers, subsequences of length k observed to have the minimum hash value across a genomic region and are therefore unique and comparable to that genomic region. The two databases are queried against each other, resulting in a list of positions where two or more sequences match. I am developing two Python applications that first, process the results of the algorithm and secondly, return a score that enable the ranking of bacterium matches. The higher the score, the better the match between the unknown bacteria and the standardized reference genome. The goal of this experiment is to show that minimizers are a fast mean of characterizing bacterial shotgun assembly contigs.
Using Cisco Network Components to Improve NIDPS Performance csandit
Network Intrusion Detection and Prevention Systems (NIDPSs) are used to detect, prevent and
report evidence of attacks and malicious traffic. Our paper presents a study where we used open
source NIDPS software. We show that NIDPS detection performance can be weak in the face of
high-speed and high-load traffic in terms of missed alerts and missed logs. To counteract this
problem, we have proposed and evaluated a solution that utilizes QoS, queues and parallel
technologies in a multi-layer Cisco Catalyst Switch to increase NIDPSs detection performance.
Our approach designs a novel QoS architecture to organise and improve throughput-forwardplan
traffic in a layer 3 switch in order to improve NIDPS performance.
Outsourced kp abe with chosen ciphertext securitycsandit
Key-Policy Attribute Based Encryption (KP-ABE) has always been criticized for its inefficiency
drawbacks. Based on the cloud computing technology, computation outsourcing is one of the
effective solution to this problem. Some papers have proposed their schemes; however,
adversaries in their attack models were divided into two categories and they are assumed not to
communicate with each other, which is obviously unrealistic. In this paper, we first proved there
exist severe security vulnerabilities in these schemes for such an assumption, and then proposed
a security enhanced Chosen Ciphertext Attack (SE-CCA) model, which eliminates the improper
limitations. By utilizing Proxy Re-Encryption (PRE) and one-time signature technology, we also
constructed a concrete KP-ABE outsourcing scheme (O-KP-ABE) and proved its security under
SE-CCA model. Comparisons with existing schemes show that our constructions have obvious
comprehensive advantages in security and efficiency.
Data mining is the knowledge discovery in databases and the gaol is to extract patterns and knowledge from
large amounts of data. The important term in data mining is text mining. Text mining extracts the quality
information highly from text. Statistical pattern learning is used to high quality information. High –quality in
text mining defines the combinations of relevance, novelty and interestingness. Tasks in text mining are text
categorization, text clustering, entity extraction and sentiment analysis. Applications of natural language
processing and analytical methods are highly preferred to turn
Presented at the Global Pharma R&D Informatics Congress. To find out more, visit:
www.global-engage.com
Text mining extracts complex information from text (entities, events and epistemic knowledge). It can be used to support pathway construction and the design of experiments by extracting evidence from literature. In this presentation, Sophia Ananiadou, Director of the National Centre for Text Mining, discusses bridging the gap between knowledge and text in cancer biology.
Abstract—Classical machine learning techniques have been employed severally in intrusion detection. But due to the rising cases and sophistication of attacks, more advanced machine learning techniques including ensemble-based methods, neural networks and deep learning techniques have been applied. However, there is still need for improved machine learning approach to detect attacks more effectively and efficiently. Stacked generalization approach has been shown to be capable of learning from features and meta-features but has been limited by the deficiencies of base classifiers and lack of optimization in the choice of meta-feature combination. This paper therefore proposes a stacked generalization ensemble approach based on two-tier meta-learner, in which the outputs of classical stacked ensemble are passed to multi-feature-based stacked ensemble, which is optimized. A Grid-search approach is used for the optimization. Nine data features and four meta-features derived from Logistic Regression, Support Vector Machine, Naïve Bayes, and Multilayer Perceptron neural network are used for the machine learning classification task. By applying neural networks as the meta-learner for the classification of NSL-KDD data, improved performances in terms of accuracy, precision, recall and F-measure of 0.97, 0.98, 0.98 and 0.98, respectively are achieved.
International Journal of Computer Science and Information Security,IJCSIS ISSN 1947-5500, Pittsburgh, PA, USA
Email: ijcsiseditor@gmail.com
http://sites.google.com/site/ijcsis/
https://google.academia.edu/JournalofComputerScience
https://www.linkedin.com/in/ijcsis-research-publications-8b916516/
http://www.researcherid.com/rid/E-1319-2016
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.
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.
DoS Forensic Exemplar Comparison to a Known SampleCSCJournals
The investigation of any event or incident often involves the evaluation of physical evidence. Occasionally, a comparison is conducted between an evidentiary sample of unknown origin and that of an appropriate known sample. In a Denial of Service (DoS) attack, items of evidentiary value may cross the spectrum from anecdotes to useful information in firewall logs or complete packet captures. Because of the spoofed or reflective nature of DoS attacks, relevant information leading to the direct identification of the perpetrator is rarely available. In many instances, this underscores the significance of the investigator's ability to accurately identify the tool utilized by the suspect. For a DoS attack scenario, this would likely involve a commercially available stresser or criminal bot infrastructure. In this paper, we propose the concept of a DoS exemplar and determine if the comparison of evidentiary samples to an appropriate known sample of DoS attributes could add value in the investigative process. We also provide a simple tool to compare two DoS flows.
AN EVALUATION OF ENERGY EFFICIENT SOURCE AUTHENTICATION METHODS FOR FALSE DA...ijsptm
The false data injection attack is a major security threat in Wireless Sensor Network (WSN) since is
degrades the network capability. The bandwidth efficient cooperative authentication (BECAN) scheme is
used for filtering the false data injection attack. It is used to save energy of sensor nodes in WSN by early
detection and filtering of maximum possible injected false data. Source authentication is a critical security
requirement in wireless sensor networks to identify attacker nodes that injects false data. Solutions based
on Elliptic Curve Cryptography (ECC) have been used for source authentication, but they suffer from
severe energy depletion. This results in high computational and communication overheads. Bloom filter
based Symmetric-key source authentication scheme exhibits low authentication overhead .This avoids the
inherent problems associated with public key cryptography based schemes. The current work demonstrates
the efficiency of bloom filter based source authentication using BECAN scheme by comparing ECC and
Bloom filter based methods in terms of energy consumption
Efficient Detection Of Selfish Node In Manet Using A Colloborative WatchdogIJERA Editor
Mobile ad-hoc networks(MANET) are collected many number of nodes.In a mobile ad-hoc network(MANET)
undertakes that all the mobile nodes unitewillingly in order to work accurately.This is a cost –intensive action
for the collaboration and particular nodes can decline to cooperate then it will prominent to a selfish node
behaviour.Thus, it will utterly affect the global network performance.The watchdogs are a well-known device
used for identifying a selfish node.Theprocedure performed by watchdogs can fail,generating false positives
and false negatives this may convince to wrong operation.Whenidentifying selfish node trusting on local
watchdogs only can prime to poor performance,in terms of precision and speed.Thus we propose collaborative
contact based watchdog(COCOWA) as a collaborative method based on the dispersion of selfish nodes
responsiveness when a contact occurs,so the evidence will quickly circulated about selfish nodes. As shown in
the paper,whenidentifying a selfish nodes this collaborative approach decreases the time and rises the precision
DETECTING PACKET DROPPING ATTACK IN WIRELESS AD HOC NETWORKIJCI JOURNAL
In wireless ad hoc network, packet loss is a serious issue. Either it is caused by link errors or by malicious
packet dropping. The malicious nodes in a route can intentionally drop the packets during the transmission
from source to destination. It is difficult to distinct the packet loss due to link errors and malicious
dropping. Here is a mechanism which will detect the malicious packet dropping by using the correlation
between packets. An auditing architecture based on homomorphic linear authenticator can be used to
ensure the proof of reception of packets at each node. Also to ensure the forwarding of packets at each
node, a reputation mechanism based on indirect reciprocity can be used.
A new clutering approach for anomaly intrusion detectionIJDKP
Recent advances in technology have made our work easier compare to earlier times. Computer network is
growing day by day but while discussing about the security of computers and networks it has always been a
major concerns for organizations varying from smaller to larger enterprises. It is true that organizations
are aware of the possible threats and attacks so they always prepare for the safer side but due to some
loopholes attackers are able to make attacks.
Intrusion detection is one of the major fields of research and researchers are trying to find new algorithms
for detecting intrusions. Clustering techniques of data mining is an interested area of research for detecting
possible intrusions and attacks. This paper presents a new clustering approach for anomaly intrusion
detection by using the approach of K-medoids method of clustering and its certain modifications. The
proposed algorithm is able to achieve high detection rate and overcomes the disadvantages of K-means
algorithm.
A HYBRID FUZZY SYSTEM BASED COOPERATIVE SCALABLE AND SECURED LOCALIZATION SCH...ijwmn
Localization entails position estimation of sensor nodes by employing different techniques and mathematical computations. Localizable sensors also form an inherent part in the functioning of IoT devices and robotics. In this article, the author extends1 a novel scheme for node localization implemented using a hybrid fuzzy logic system to trace the node locations inside the deployment region, presented by the
Abhishek Kumar et. al. The results obtained were then optimized using Gauss Newton Optimization to improve the localization accuracy by 50% to 90% vis-à-vis weighted centroid and other fuzzy based localization algorithms. This article attempts to scale the proposed scheme for large number of sensor nodes to emulate somewhat real world scenario by introducing cooperative localization in previous presented work. The study also analyses the effectiveness of such scaling by comparing the localization accuracy. In next section, the article incorporates security in the proposed cooperative localization approach to detect malicious nodes/anchors by mutual authentication using El Gamel digital Signature scheme. A detailed study of the impact of incorporating security and scaling on average processing time and localization coverage has also been performed. The processing time increased by a factor of 2.5s for 500 nodes (can be attributed to more number of iterations and computations and large deployment area with small radio range of nodes) and coverage remained almost equal, albeit slightly low by a factor of 1% to 2%. Apart from these, the article also discusses the impact of adding extra functionalities in the proposed hybrid fuzzy system based localization scheme on processing time and localization accuracy.Lastly, this study also briefs about how the proposed scalable, cooperative and secure localization scheme tackles the type of attacks that pose threat to localization.
Secret key extraction from wireless signal strength in real environmentsMuthu Sybian
Sybian Technologies is a leading IT services provider & custom software development company. We offer full cycle custom software development services, from product idea, offshore software development to outsourcing support & enhancement. Sybian employs a knowledgeable group of software developers coming from different backgrounds. We are able to balance product development efforts & project duration to your business needs.
Sybian Technologies invests extensively in R&D to invent new solutions for ever changing needs of your businesses, to make it future-proof, sustainable and consistent. We work in close collaboration with academic institutions and research labs across the world to design, implement and support latest IT based solutions that are futuristic, progressive and affordable. Our services continue to earn trust and loyalty from its clients through its commitment to the following parameters
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
A predictive model for network intrusion detection using stacking approach IJECEIAES
Due to the emerging technological advances, cyber-attacks continue to hamper information systems. The changing dimensionality of cyber threat landscape compel security experts to devise novel approaches to address the problem of network intrusion detection. Machine learning algorithms are extensively used to detect intrusions by dint of their remarkable predictive power. This work presents an ensemble approach for network intrusion detection using a concept called Stacking. As per the popular no free lunch theorem of machine learning, employing single classifier for a problem at hand may not be ideal to achieve generalization. Therefore, the proposed work on network intrusion detection emphasizes upon a combinative approach to improve performance. A robust processing paradigm called Graphlab Create, capable of upholding massive data has been used to implement the proposed methodology. Two benchmark datasets like UNSW NB-15 and UGR’ 16 datasets are considered to demonstrate the validity of predictions. Empirical investigation has illustrated that the performance of the proposed approach has been reasonably good. The contribution of the proposed approach lies in its finesse to generate fewer misclassifications pertaining to various attack vectors considered in the study.
Presented at the Global Pharma R&D Informatics Congress. To find out more, visit:
www.global-engage.com
Text mining extracts complex information from text (entities, events and epistemic knowledge). It can be used to support pathway construction and the design of experiments by extracting evidence from literature. In this presentation, Sophia Ananiadou, Director of the National Centre for Text Mining, discusses bridging the gap between knowledge and text in cancer biology.
Abstract—Classical machine learning techniques have been employed severally in intrusion detection. But due to the rising cases and sophistication of attacks, more advanced machine learning techniques including ensemble-based methods, neural networks and deep learning techniques have been applied. However, there is still need for improved machine learning approach to detect attacks more effectively and efficiently. Stacked generalization approach has been shown to be capable of learning from features and meta-features but has been limited by the deficiencies of base classifiers and lack of optimization in the choice of meta-feature combination. This paper therefore proposes a stacked generalization ensemble approach based on two-tier meta-learner, in which the outputs of classical stacked ensemble are passed to multi-feature-based stacked ensemble, which is optimized. A Grid-search approach is used for the optimization. Nine data features and four meta-features derived from Logistic Regression, Support Vector Machine, Naïve Bayes, and Multilayer Perceptron neural network are used for the machine learning classification task. By applying neural networks as the meta-learner for the classification of NSL-KDD data, improved performances in terms of accuracy, precision, recall and F-measure of 0.97, 0.98, 0.98 and 0.98, respectively are achieved.
International Journal of Computer Science and Information Security,IJCSIS ISSN 1947-5500, Pittsburgh, PA, USA
Email: ijcsiseditor@gmail.com
http://sites.google.com/site/ijcsis/
https://google.academia.edu/JournalofComputerScience
https://www.linkedin.com/in/ijcsis-research-publications-8b916516/
http://www.researcherid.com/rid/E-1319-2016
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.
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.
DoS Forensic Exemplar Comparison to a Known SampleCSCJournals
The investigation of any event or incident often involves the evaluation of physical evidence. Occasionally, a comparison is conducted between an evidentiary sample of unknown origin and that of an appropriate known sample. In a Denial of Service (DoS) attack, items of evidentiary value may cross the spectrum from anecdotes to useful information in firewall logs or complete packet captures. Because of the spoofed or reflective nature of DoS attacks, relevant information leading to the direct identification of the perpetrator is rarely available. In many instances, this underscores the significance of the investigator's ability to accurately identify the tool utilized by the suspect. For a DoS attack scenario, this would likely involve a commercially available stresser or criminal bot infrastructure. In this paper, we propose the concept of a DoS exemplar and determine if the comparison of evidentiary samples to an appropriate known sample of DoS attributes could add value in the investigative process. We also provide a simple tool to compare two DoS flows.
AN EVALUATION OF ENERGY EFFICIENT SOURCE AUTHENTICATION METHODS FOR FALSE DA...ijsptm
The false data injection attack is a major security threat in Wireless Sensor Network (WSN) since is
degrades the network capability. The bandwidth efficient cooperative authentication (BECAN) scheme is
used for filtering the false data injection attack. It is used to save energy of sensor nodes in WSN by early
detection and filtering of maximum possible injected false data. Source authentication is a critical security
requirement in wireless sensor networks to identify attacker nodes that injects false data. Solutions based
on Elliptic Curve Cryptography (ECC) have been used for source authentication, but they suffer from
severe energy depletion. This results in high computational and communication overheads. Bloom filter
based Symmetric-key source authentication scheme exhibits low authentication overhead .This avoids the
inherent problems associated with public key cryptography based schemes. The current work demonstrates
the efficiency of bloom filter based source authentication using BECAN scheme by comparing ECC and
Bloom filter based methods in terms of energy consumption
Efficient Detection Of Selfish Node In Manet Using A Colloborative WatchdogIJERA Editor
Mobile ad-hoc networks(MANET) are collected many number of nodes.In a mobile ad-hoc network(MANET)
undertakes that all the mobile nodes unitewillingly in order to work accurately.This is a cost –intensive action
for the collaboration and particular nodes can decline to cooperate then it will prominent to a selfish node
behaviour.Thus, it will utterly affect the global network performance.The watchdogs are a well-known device
used for identifying a selfish node.Theprocedure performed by watchdogs can fail,generating false positives
and false negatives this may convince to wrong operation.Whenidentifying selfish node trusting on local
watchdogs only can prime to poor performance,in terms of precision and speed.Thus we propose collaborative
contact based watchdog(COCOWA) as a collaborative method based on the dispersion of selfish nodes
responsiveness when a contact occurs,so the evidence will quickly circulated about selfish nodes. As shown in
the paper,whenidentifying a selfish nodes this collaborative approach decreases the time and rises the precision
DETECTING PACKET DROPPING ATTACK IN WIRELESS AD HOC NETWORKIJCI JOURNAL
In wireless ad hoc network, packet loss is a serious issue. Either it is caused by link errors or by malicious
packet dropping. The malicious nodes in a route can intentionally drop the packets during the transmission
from source to destination. It is difficult to distinct the packet loss due to link errors and malicious
dropping. Here is a mechanism which will detect the malicious packet dropping by using the correlation
between packets. An auditing architecture based on homomorphic linear authenticator can be used to
ensure the proof of reception of packets at each node. Also to ensure the forwarding of packets at each
node, a reputation mechanism based on indirect reciprocity can be used.
A new clutering approach for anomaly intrusion detectionIJDKP
Recent advances in technology have made our work easier compare to earlier times. Computer network is
growing day by day but while discussing about the security of computers and networks it has always been a
major concerns for organizations varying from smaller to larger enterprises. It is true that organizations
are aware of the possible threats and attacks so they always prepare for the safer side but due to some
loopholes attackers are able to make attacks.
Intrusion detection is one of the major fields of research and researchers are trying to find new algorithms
for detecting intrusions. Clustering techniques of data mining is an interested area of research for detecting
possible intrusions and attacks. This paper presents a new clustering approach for anomaly intrusion
detection by using the approach of K-medoids method of clustering and its certain modifications. The
proposed algorithm is able to achieve high detection rate and overcomes the disadvantages of K-means
algorithm.
A HYBRID FUZZY SYSTEM BASED COOPERATIVE SCALABLE AND SECURED LOCALIZATION SCH...ijwmn
Localization entails position estimation of sensor nodes by employing different techniques and mathematical computations. Localizable sensors also form an inherent part in the functioning of IoT devices and robotics. In this article, the author extends1 a novel scheme for node localization implemented using a hybrid fuzzy logic system to trace the node locations inside the deployment region, presented by the
Abhishek Kumar et. al. The results obtained were then optimized using Gauss Newton Optimization to improve the localization accuracy by 50% to 90% vis-à-vis weighted centroid and other fuzzy based localization algorithms. This article attempts to scale the proposed scheme for large number of sensor nodes to emulate somewhat real world scenario by introducing cooperative localization in previous presented work. The study also analyses the effectiveness of such scaling by comparing the localization accuracy. In next section, the article incorporates security in the proposed cooperative localization approach to detect malicious nodes/anchors by mutual authentication using El Gamel digital Signature scheme. A detailed study of the impact of incorporating security and scaling on average processing time and localization coverage has also been performed. The processing time increased by a factor of 2.5s for 500 nodes (can be attributed to more number of iterations and computations and large deployment area with small radio range of nodes) and coverage remained almost equal, albeit slightly low by a factor of 1% to 2%. Apart from these, the article also discusses the impact of adding extra functionalities in the proposed hybrid fuzzy system based localization scheme on processing time and localization accuracy.Lastly, this study also briefs about how the proposed scalable, cooperative and secure localization scheme tackles the type of attacks that pose threat to localization.
Secret key extraction from wireless signal strength in real environmentsMuthu Sybian
Sybian Technologies is a leading IT services provider & custom software development company. We offer full cycle custom software development services, from product idea, offshore software development to outsourcing support & enhancement. Sybian employs a knowledgeable group of software developers coming from different backgrounds. We are able to balance product development efforts & project duration to your business needs.
Sybian Technologies invests extensively in R&D to invent new solutions for ever changing needs of your businesses, to make it future-proof, sustainable and consistent. We work in close collaboration with academic institutions and research labs across the world to design, implement and support latest IT based solutions that are futuristic, progressive and affordable. Our services continue to earn trust and loyalty from its clients through its commitment to the following parameters
Final Year Projects & Real Time live Projects
JAVA(All Domains)
DOTNET(All Domains)
ANDROID
EMBEDDED
VLSI
MATLAB
Project Support
Abstract, Diagrams, Review Details, Relevant Materials, Presentation,
Supporting Documents, Software E-Books,
Software Development Standards & Procedure
E-Book, Theory Classes, Lab Working Programs, Project Design & Implementation
24/7 lab session
Final Year Projects For BE,ME,B.Sc,M.Sc,B.Tech,BCA,MCA
PROJECT DOMAIN:
Cloud Computing
Networking
Network Security
PARALLEL AND DISTRIBUTED SYSTEM
Data Mining
Mobile Computing
Service Computing
Software Engineering
Image Processing
Bio Medical / Medical Imaging
Contact Details:
Sybian Technologies Pvt Ltd,
No,33/10 Meenakshi Sundaram Building,
Sivaji Street,
(Near T.nagar Bus Terminus)
T.Nagar,
Chennai-600 017
Ph:044 42070551
Mobile No:9790877889,9003254624,7708845605
Mail Id:sybianprojects@gmail.com,sunbeamvijay@yahoo.com
A predictive model for network intrusion detection using stacking approach IJECEIAES
Due to the emerging technological advances, cyber-attacks continue to hamper information systems. The changing dimensionality of cyber threat landscape compel security experts to devise novel approaches to address the problem of network intrusion detection. Machine learning algorithms are extensively used to detect intrusions by dint of their remarkable predictive power. This work presents an ensemble approach for network intrusion detection using a concept called Stacking. As per the popular no free lunch theorem of machine learning, employing single classifier for a problem at hand may not be ideal to achieve generalization. Therefore, the proposed work on network intrusion detection emphasizes upon a combinative approach to improve performance. A robust processing paradigm called Graphlab Create, capable of upholding massive data has been used to implement the proposed methodology. Two benchmark datasets like UNSW NB-15 and UGR’ 16 datasets are considered to demonstrate the validity of predictions. Empirical investigation has illustrated that the performance of the proposed approach has been reasonably good. The contribution of the proposed approach lies in its finesse to generate fewer misclassifications pertaining to various attack vectors considered in the study.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
We would send hard copy of Journal by speed post to the address of correspondence author after online publication of paper.
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3 S W 2009 I E E E Abstracts Java, N C C T Chennaincct
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final Year Projects, Final Year Projects in Chennai, Software Projects, Embedded Projects, Microcontrollers Projects, DSP Projects, VLSI Projects, Matlab Projects, Java Projects, .NET Projects, IEEE Projects, IEEE 2009 Projects, IEEE 2009 Projects, Software, IEEE 2009 Projects, Embedded, Software IEEE 2009 Projects, Embedded IEEE 2009 Projects, Final Year Project Titles, Final Year Project Reports, Final Year Project Review, Robotics Projects, Mechanical Projects, Electrical Projects, Power Electronics Projects, Power System Projects, Model Projects, Java Projects, J2EE Projects, Engineering Projects, Student Projects, Engineering College Projects, MCA Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, Wireless Networks Projects, Network Security Projects, Networking Projects, final year projects, ieee projects, student projects, college projects, ieee projects in chennai, java projects, software ieee projects, embedded ieee projects, "ieee2009projects", "final year projects", "ieee projects", "Engineering Projects", "Final Year Projects in Chennai", "Final year Projects at Chennai", Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, Final Year Java Projects, Final Year ASP.NET Projects, Final Year VB.NET Projects, Final Year C# Projects, Final Year Visual C++ Projects, Final Year Matlab Projects, Final Year NS2 Projects, Final Year C Projects, Final Year Microcontroller Projects, Final Year ATMEL Projects, Final Year PIC Projects, Final Year ARM Projects, Final Year DSP Projects, Final Year VLSI Projects, Final Year FPGA Projects, Final Year CPLD Projects, Final Year Power Electronics Projects, Final Year Electrical Projects, Final Year Robotics Projects, Final Year Solor Projects, Final Year MEMS Projects, Final Year J2EE Projects, Final Year J2ME Projects, Final Year AJAX Projects, Final Year Structs Projects, Final Year EJB Projects, Final Year Real Time Projects, Final Year Live Projects, Final Year Student Projects, Final Year Engineering Projects, Final Year MCA Projects, Final Year MBA Projects, Final Year College Projects, Final Year BE Projects, Final Year BTech Projects, Final Year ME Projects, Final Year MTech Projects, Final Year M.Sc Projects, IEEE Java Projects, ASP.NET Projects, VB.NET Projects, C# Projects, Visual C++ Projects, Matlab Projects, NS2 Projects, C Projects, Microcontroller Projects, ATMEL Projects, PIC Projects, ARM Projects, DSP Projects, VLSI Projects, FPGA Projects, CPLD Projects, Power Electronics Projects, Electrical Projects, Robotics Projects, Solor Projects, MEMS Projects, J2EE Projects, J2ME Projects, AJAX Projects, Structs Projects, EJB Projects, Real Time Projects, Live Projects, Student Projects, Engineering Projects, MCA Projects, MBA Projects, College Projects, BE Projects, BTech Projects, ME Projects, MTech Projects, M.Sc Projects, IEEE 2009 Java Projects, IEEE 2009 ASP.NET Projects, IEEE 2009 VB.NET Projects, IEEE 2009 C# Projects, IEEE 2009 Visual C++ Projects, IEEE 2009 Matlab Projects, IEEE 2009 NS2 Projects, IEEE 2009 C Projects, IEEE 2009 Microcontroller Projects, IEEE 2009 ATMEL Projects, IEEE 2009 PIC Projects, IEEE 2009 ARM Projects, IEEE 2009 DSP Projects, IEEE 2009 VLSI Projects, IEEE 2009 FPGA Projects, IEEE 2009 CPLD Projects, IEEE 2009 Power Electronics Projects, IEEE 2009 Electrical Projects, IEEE 2009 Robotics Projects, IEEE 2009 Solor Projects, IEEE 2009 MEMS Projects, IEEE 2009 J2EE P
M.Phil Computer Science Wireless Communication ProjectsVijay Karan
List of Wireless Communication IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Wireless Communication for M.Phil Computer Science students.
M.E Computer Science Wireless Communication ProjectsVijay Karan
List of Wireless Communication IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Wireless Communication for M.E Computer Science students.
M.Phil Computer Science Parallel and Distributed System ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for M.Phil Computer Science students.
M.E Computer Science Parallel and Distributed System ProjectsVijay Karan
List of Parallel and Distributed System IEEE 2006 Projects. It Contains the IEEE Projects in the Domain Parallel and Distributed System for M.E Computer Science students.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
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Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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"Protectable subject matters, Protection in biotechnology, Protection of othe...
IEEE 2015 Java Projects
1. IEEE 2015 Java Projects
Web : www.kasanpro.com Email : sales@kasanpro.com
List Link : http://kasanpro.com/projects-list/ieee-2015-java-projects
Title :Differential Phase-Shift Quantum Key Distribution Systems
Language : Java
Project Link : http://kasanpro.com/p/java/differential-phase-shift-quantum-key-distribution-systems
Abstract : Differential phase-shift (DPS) quantum key distribution (QKD) is a unique QKD protocol that is different
from traditional ones, featuring simplicity and practicality. This paper overviews DPS-QKD systems.
Title :Safeguarding Quantum Key Distribution Through Detection Randomization
Language : Java
Project Link : http://kasanpro.com/p/java/safeguarding-quantum-key-distribution-through-detection-randomization
Abstract : We propose and experimentally demonstrate a scheme to render the detection apparatus of a quantum
key distribution system immune to the main classes of hacking attacks in which the eavesdropper explores the
back-door opened by the single-photon detectors. The countermeasure is based on the creation of modes that are not
deterministically accessible to the eavesdropper. We experimentally show that the use of beamsplitters and extra
single-photon detectors at the receiver station passively creates randomized spatial modes that erase any knowledge
the eavesdropper might have gained when using bright-light faked states. Additionally, we experimentally show a
detectorscrambling approach where the random selection of the detector used for each measurement--equivalent to
an active spatial mode randomization--hashes out the side-channel open by the detection efficiency mismatch-based
attacks. The proposed combined countermeasure represents a practical and readily implementable solution against
the main classes of quantum hacking attacks aimed on the single-photon detector so far, without intervening on the
inner working of the devices.
Title :Postprocessing of the Oblivious Key in Quantum Private Query
Language : Java
Project Link : http://kasanpro.com/p/java/oblivious-key-postprocessing-quantum-private-query
Abstract : Private query is a kind of cryptographic protocols to protect both users' privacies in their communication.
For instance, Alice wants to buy one item from Bob's database. The aim of private query is to ensure that Alice can
get only one item from Bob, and simultaneously, Bob cannot know which one was taken by Alice. In pursuing high
security and efficiency, some quantum private query protocols were proposed. As a practical model, Quantum-
Oblivious-Key-Transfer (QOKT)-based private query, which utilizes a QOKT protocol to distribute oblivious key
between Alice and Bob and then applies the key to achieve the aim of private query, has drawn much attention. Here,
we focus on postprocessing of the oblivious key, and the following two contributions are achieved. 1) We analyze
three recently proposed dilution methods and find two of them have serious security loophole. That is, Alice can
illegally obtain much additional information about Bob's database by multiple queries. For example, Alice can obtain
the whole database, which contains 104 items, by only 53.4 queries averagely. 2) We present an effective
error-correction method for the oblivious key, which can address the realistic scenario with channel noises and make
QOKT-based private query more practical.
IEEE 2015 Java Projects
Title :Rank-Based Similarity Search: Reducing the Dimensional Dependence
Language : Java
Project Link : http://kasanpro.com/p/java/rank-based-similarity-search-reducing-dimensional-dependence
Abstract : This paper introduces a data structure for k-NN search, the Rank Cover Tree (RCT), whose pruning tests
rely solely on the comparison of similarity values; other properties of the underlying space, such as the triangle
inequality, are not employed. Objects are selected according to their ranks with respect to the query object, allowing
much tighter control on the overall execution costs. A formal theoretical analysis shows that with very high probability,
the RCT returns a correct query result in time that depends very competitively on a measure of the intrinsic
dimensionality of the data set. The experimental results for the RCT show that non-metric pruning strategies for
similarity search can be practical even when the representational dimension of the data is extremely high. They also
show that the RCT is capable of meeting or exceeding the level of performance of state-of-the-art methods that make
use of metric pruning or other selection tests involving numerical constraints on distance values.
Title :Medical Data Compression and Transmission in Wireless Ad Hoc Networks
Language : Java
Project Link : http://kasanpro.com/p/java/medical-data-compression-transmission-wireless-ad-hoc-networks
Abstract : A wireless ad hoc network (WANET) is a type of wireless network aimed to be deployed in a disaster area
2. in order to collect data of patients and improve medical facilities. The WANETs are composed of several small nodes
scattered in the disaster area. The nodes are capable of sending (wirelessly) the collected medical data to the base
stations. The limited battery power of nodes and the transmission of huge medical data require an energy efficient
approach to preserve the quality of service of WANETs. To address this issue, we propose an optimizationbased
medical data compression technique, which is robust to transmission errors. We propose a fuzzy-logic-based route
selection technique to deliver the compressed data that maximizes the lifetime of WANETs. The technique is fully
distributed and does not use any geographical/location information. We demonstrate the utility of the proposed work
with simulation results. The results show that the proposed work effectively maintains connectivity of WANETs and
prolongs network lifetime.
Title :Towards Effective Bug Triage with Software Data Reduction Techniques
Language : Java
Project Link : http://kasanpro.com/p/java/bug-triage-software-data-reduction-techniques
Abstract : Software companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of
fixing bugs is bug triage, which aims to correctly assign a developer to a new bug. To decrease the time cost in
manual work, text classification techniques are applied to conduct automatic bug triage. In this paper, we address the
problemof data reduction for bug triage, i.e., how to reduce the scale and improve the quality of bug data.We combine
instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word
dimension. To determine the order of applying instance selection and feature selection, we extract attributes from
historical bug data sets and build a predictive model for a new bug data set. We empirically investigate the
performance of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and
Mozilla. The results show that our data reduction can effectively reduce the data scale and improve the accuracy of
bug triage. Our work provides an approach to leveraging techniques on data processing to form reduced and
high-quality bug data in software development and maintenance.
IEEE 2015 Java Projects