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- S. Shanmugavel
- D. Suganya Devi
- K. Srinivasa Rao
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- V. S. Meenakshi
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- Shahnaz Bathul
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Journals
- Indian Journal of Science and Technology
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A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Padmavathi, G.
- Performance Analysis of Cooperative Spectrum Sensing Technique for Low SNR Regime over Fading Channels for Cognitive Radio Networks
Abstract Views :275 |
PDF Views:0
Authors
Affiliations
1 Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur - 602117, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti - 628503, Tamil Nadu, IN
1 Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Sriperumbudur - 602117, Tamil Nadu, IN
2 Department of Electronics and Communication Engineering, National Engineering College, Kovilpatti - 628503, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 8, No 16 (2015), Pagination:Abstract
Cognitive Radio is a technology for Next Generation Wireless Networks to support Dynamic Spectrum Access which addresses the spectrum scarcity and under utilization problems experienced by today’s wireless communication networks. Spectrum Sensing is an important function of cognitive radio that identifies the unused licensed frequency bands of Primary Users for opportunistic access by Secondary Users. In this paper, we have proposed a sensing technique incorporating wavelet denoising to enhance the sensing performance at low SNR regime. The combination of wavelet denoising preceeding energy detector, hard decision for local sensing and OR fusion rule at the fusion center for cooperative sensing has improved the sensing performance. We have quantified the performance improvement of the proposed technique in fading environments and studied the effect of wavelet denoising. Probability of missed detection has been reduced by 38% over Rayleigh Fading channel and 52% over Nakagami Fading channel compared to conventional sensing technique for ten users cooperation. Sensing time has been reduced by 1 msec and throughput improved by 50 Mbits/Sec/Hz compared to conventional energy detection based sensing method.Keywords
Cognitive Radio, Cooperative Spectrum Sensing, Energy Detection, Hard Decision, Wavelet DenoisingFull Text
- Performance Evaluation and Enhancement of OMCT Algorithm in MANET
Abstract Views :197 |
PDF Views:2
Authors
Affiliations
1 SNR Sons College, Coimbatore-06, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
1 SNR Sons College, Coimbatore-06, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
Source
Wireless Communication, Vol 1, No 1 (2009), Pagination: 27-31Abstract
Many emerging applications in mobile adhoc networks involve group-oriented communication. Multicast is an efficient means of distributing data to a group of participants. Key management is the fundamental challenge in designing secure multicast communications. In many group interactions, new member can join and current members can leave at any time and existing members must communicate securely using multicast key distribution. This has to overcome the challenging element of "1affects n" phenomenon. To solve this problem, multicast clustering is the best solution. This paper presents an efficient clustering approach for secure multicast key distribution in mobile adhoc networks. The construction of clusters is based on localization and mobility of nodes. The proposal of this paper is to enhance OMCT (Optimized Multicast Cluster Tree) by integrating with DSDV (Destination Sequenced Distance Vector) routing protocol, which makes easy to elect the Local Controllers of the clusters and updates periodically as the node joins and leaves the cluster. The proposed model is simulated and its performance is evaluated in terms of average latency of key delivery, energy consumption and key delivery ratio. Thus this approach ensures a fast and efficient clustering approach for secure multicast key distribution in mobile adhoc networks compared to OMCT algorithm.Keywords
Key Distribution, Multicast, Clustering, OMCT, DSDV and MANET.
- Performance Evaluation of Parallel and Series Communication Network with Dynamic Bandwidth Allocation
Abstract Views :157 |
PDF Views:2
Authors
Affiliations
1 Department of Technical Education, AP, IN
2 Department of Statistics, Andhra University, Visakhapatnam, IN
3 Electronics and Communication Engineering, Andhra University, Visakhapatnam, IN
1 Department of Technical Education, AP, IN
2 Department of Statistics, Andhra University, Visakhapatnam, IN
3 Electronics and Communication Engineering, Andhra University, Visakhapatnam, IN
Source
Networking and Communication Engineering, Vol 1, No 7 (2009), Pagination: 410-421Abstract
In this paper a parallel and series communication network model with dynamic bandwidth allocation is developed and analyzed. In order to reduce congestion in buffer and to improve voice quality several congestion control methods like bit dropping,selective packet discarding, flow control etc., are developed and successfully implemented. to have an efficient utilization we propose dynamic allocation of bandwidth i.e. the transmission rate of the data/voice packet dependent on the content of the buffer just before it get transmitted. The end to-end performance of the model is measured by approximating the arrival and service processes of the packets follow poisson process. The transient analysis of the communication network shows that dynamic allocation has a significant effect in reducing mean delays and improving throughput of the transmitter. Graphs illustrate performance of the network model for different parameters.
Keywords
Dynamic Bandwidth Allocation, Joint Probability Generating Function, Mean Delay, Poisson Process, Throughput.- An Evaluation of Suitable Key Management Schemes in Mobile Adhoc Networks
Abstract Views :153 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, Avinashilingam University for Women, Coimbatore–641 043, IN
2 Department of Computer Science, Avinashilingam University for Women, Coimbatore – 641 043, IN
1 Department of Computer Science, Avinashilingam University for Women, Coimbatore–641 043, IN
2 Department of Computer Science, Avinashilingam University for Women, Coimbatore – 641 043, IN
Source
Networking and Communication Engineering, Vol 1, No 2 (2009), Pagination: 62-66Abstract
Mobile ad hoc networks, or MANETs, are wireless networks that do not depend on a fixed infrastructure. Mobile nodes may form networks on the fly for a variety of environments including emergency rescue missions, sensor networks, military applications,and open networks of personal wireless devices. Wireless nodes can communicate directly with neighboring nodes that are within their transmission ranges. To reach nodes outside the direct transmission range, nodes depend on each other to forward their packets, creating
a multihop network with many vulnerability points. Cryptographic techniques are essential to the protection of both routing information and application data. A secure and efficient management of cryptographic keys is crucial for a reliable network service and thus the success for wireless ad hoc networks. This paper evaluates and surveys the key management schemes available for mobile adhoc network.
Keywords
Mobile ad hoc Network, Key Management, Public Key Scheme, Symmetric Key Scheme, Security.- A Survey on Biometric Template Protection Using Hybrid Approaches
Abstract Views :137 |
PDF Views:4
Authors
Affiliations
1 Department of Computer Applications, SNR Sons College, Coimbatore-641006, IN
1 Department of Computer Applications, SNR Sons College, Coimbatore-641006, IN
Source
Biometrics and Bioinformatics, Vol 3, No 3 (2011), Pagination: 125-128Abstract
Biometric authentication due to its merits compared to traditional authentication methods like password finds its application in several crucial applications like border security, military, network security and forensic applications. However, biometric authentication systems are subjected to several attacks. Providing security to biometric template is an important issue in any biometric authentication system. Different biometric template protection mechanisms are in practice. Anyhow, no single method provides all the required properties of a biometric template. Hybrid template protection mechanisms are better compared to single biometric template protection mechanism. This paper presents a survey of different works that provides hybrid biometric template security.Keywords
Biometric Template Security, Biometric Template Protection Schemes, Hybrid Approach, Attacks.- A Survey on Biometric Template Protection Using Fuzzy Vault Scheme
Abstract Views :154 |
PDF Views:3
Authors
Affiliations
1 Department of Computer Applications, SNR Sons College, Coimbatore-641006, IN
2 Department of Computer Science, Avinashilingam Deemed University for Women, Coimbatore-641043, IN
1 Department of Computer Applications, SNR Sons College, Coimbatore-641006, IN
2 Department of Computer Science, Avinashilingam Deemed University for Women, Coimbatore-641043, IN
Source
Biometrics and Bioinformatics, Vol 3, No 1 (2011), Pagination: 33-36Abstract
Security is an important component in any authentication system. Biometric authentication is gaining much importance in the current linked scenario. Anyhow, biometric based authentication systems are subjected to a variety of attacks. Stored biometric template attack is one of the severe attacks. Biometric template plays a vital role in biometric authentication. Therefore, ensuring security to biometric template is a demanding issue in the present times. Fuzzy vault is a crypto biometric frame work that provides security to biometric templates. This paper presents a survey on the different work done on fuzzy vault scheme to protect biometric templates.Keywords
Biometric Template, Security, Fuzzy Vault, Attacks, Cryptography.- Security Analysis of Multimodal Biometric Fuzzy Vault
Abstract Views :123 |
PDF Views:8
Authors
Affiliations
1 SNR Sons College, Coimbatore - 6, IN
2 Avinashilingam University for Women, Coimbatore - 43, IN
1 SNR Sons College, Coimbatore - 6, IN
2 Avinashilingam University for Women, Coimbatore - 43, IN
Source
Biometrics and Bioinformatics, Vol 2, No 3 (2010), Pagination: 47-52Abstract
Crypto biometric systems are authentication systems where the concept of biometric authentication is blended with cryptography. Crypto-biometric systems utilize the advantages of biometrics over traditional password based authentication. This paper uses the idea of fuzzy vault cryptographic constructs to protect crucial data like secret encryption key. Fuzzy vault is a proven emerging technology for providing biometric template security. This work constructs two independent fingerprint and iris vaults and a combined multimodal biometric vault. The proposed multimodal biometric fuzzy vault uses the features extracted from both finger print and iris for ensuring high security of the critical data and the biometric template. It is comparatively difficult for an attacker to compromise multi modal biometric fuzzy vault system than single biometric fuzzy vault systems. This work measures the security of the constructed fuzzy vault by means of min-entropy.
Keywords
Biometrics, Multi Biometrics, Fuzzy Vault, Multi Biometric Fuzzy Vault, Biometric Template Security, Min-Entropy, Crypto Biometric Systems.- Security Analysis of Multimodal Biometric Fuzzy Vault
Abstract Views :144 |
PDF Views:3
Authors
Affiliations
1 SNR Sons College, Coimbatore-6, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
1 SNR Sons College, Coimbatore-6, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
Source
Biometrics and Bioinformatics, Vol 1, No 1 (2009), Pagination: 16-21Abstract
Crypto biometric systems are authentication systems where the concept of biometric authentication is blended with cryptography. Crypto-biometric systems utilize the advantages of biometrics over traditional password based authentication. This paper uses the idea of fuzzy vault cryptographic constructs to protect crucial data like secret encryption key. Fuzzy vault is a proven emerging technology for providing biometric template security. This work constructs two independent fingerprint and iris vaults and a combined multimodal biometric vault. The proposed multimodal biometric fuzzy vault uses the features extracted from both finger print and iris for ensuring high security of the critical data and the biometric template. It is comparatively difficult for an attacker to compromise multi modal biometric fuzzy vault system than single biometric fuzzy vault systems. This work measures the security of the constructed fuzzy vault by means of min-entropy.Keywords
Biometrics, Multi Biometrics, Fuzzy Vault, Multi Biometric Fuzzy Vault, Biometric Template Security, Min-Entropy, Crypto Biometric Systems.- User Identification Using Keystroke Dynamics
Abstract Views :150 |
PDF Views:2
Authors
Affiliations
1 Avinashilingam University for Women, Coimbatore, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
1 Avinashilingam University for Women, Coimbatore, IN
2 Avinashilingam University for Women, Coimbatore-43, IN
Source
Biometrics and Bioinformatics, Vol 1, No 1 (2009), Pagination: 22-26Abstract
Keyboard Entropy is a feature, which will try to identify the authenticity of a user when the user is working via a keyboard. The authentication process is done by observing the change in the entropy of the user. The objective of the paper is to design and implement a biometric authentication scheme by means of keyboard entropy to secure all applications, which require password authentication. Username and password pairs as authentication factors are as weak as they are ubiquitous. Use of a single factor of authentication is so weak that multi factor authentication methods are required. The tolerance factor provides a bit of leniency to check the authenticity of user. It is introduced in the master data depending upon how much deviation is caused by the user at different times. This paper proposes two formulae for calculating tolerance value which generates False Acceptance rate (FAR) and False Rejection Rate (FRR).Keywords
Biometric, Entropy, False Acceptance Rate, False Rejection Rate.- Stability Analysis of Discrete-Time Bidirectional Associative Neural Networks with Hysteresis
Abstract Views :202 |
PDF Views:2
Authors
Affiliations
1 Department of Mathematics, JNTU Hyderabad, IN
2 Department of Computer Science, VNRVJIET, Hyderabad, IN
1 Department of Mathematics, JNTU Hyderabad, IN
2 Department of Computer Science, VNRVJIET, Hyderabad, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 4, No 7 (2012), Pagination: 429-438Abstract
In this paper continuous hysteretic neuron model has been studied and discretized the model by using proper approximation. Sufficient condition for global exponential stability of a unique equilibrium is obtained. Motivated by the applications of bidirectional associative neural networks with hysteresis in artificial neural networks, we studied the global dynamics of bidirectional associative neural network with hysteresis. The hysteretic neural network model is envisaged to be efficient and robust for various applications such as medical image processing, military data processing, etc. Hysteretic feedback control phenomena also manage glucose vs. lactose utilization preference in Escherichia coli and ensure unidirectional cell-cycle progression in eukaryotes. The result improves the earlier publications due to the bidirectional associative memory and it removes restrictions on the neutral delays. Our result shows that after discretization of hysteretic neuron models, the network converges to a stable state and this result has been applied through numerical example. The outcomes are explicit in the sense that the criteria obtained are easily verifiable as they are expressed in terms of the parameters of the system.Keywords
Descretization, Hysteretic Neural Network, Bidirectional Associative, Global Exponential Stability.- Malicious Traffic Detection and Containment based on Connection Attempt Failures using Kernelized ELM with Automated Worm Containment Algorithm
Abstract Views :157 |
PDF Views:0
Authors
S. Divya
1,
G. Padmavathi
2
Affiliations
1 Faculty of Computer Science and Multimedia, Lincoln University College, Selangor, MY
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women,University, Coimbatore - 641043, Tamil Nadu, IN
1 Faculty of Computer Science and Multimedia, Lincoln University College, Selangor, MY
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women,University, Coimbatore - 641043, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 41 (2016), Pagination:Abstract
Objectives: In the world of Internet today, most of the communications are done through Internet applications. Rapidly with the growth of Internet, the security threat on Internet is also increasing. Internet worms are one of the serious dangerous threats heavy financial losses. To overcome these damages, the proposed methodology provide better defense mechanism through Internet worm detection and containment schemes based on connection attempt failures characteristic. Method: The Internet worm detection is done using the Machine Learning Method based on Anomaly detection schemes and containment based on blocking schemes. The proposed kernelized Extreme Learning Machine with Automated Worm Containment Algorithm (kEA) method is used for detection and containment of malicious traffic from non-existing IP addresses based on connection attempt failures. Findings: Second channel based propagation through botnet worms propagates illegal traffic from malicious IP addresses through connection attempt failures. This traffic is transferred through TCP and UDP transmission schemes. The proposed work is used to identify the second channel propagating worms and containment of malicious traffic. Improvement: The proposed kernelized Extreme Learning Machine (kELM) method achieved detection accuracy improved by 23.67%. Then proposed kEA method blocks all the detected malicious IP addresses with 100% containment at the time span of 33 ms.Keywords
Connection Attempt Failures, Kernelized ELM, Malicious IP.Full Text
- A Brief Study on Different Intrusions and Machine Learning-Based Anomaly Detection Methods in Wireless Sensor Networks
Abstract Views :299 |
PDF Views:4
Authors
J. Saranya
1,
G. Padmavathi
1
Affiliations
1 Dept. of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, IN
1 Dept. of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, IN
Source
International Journal of Advanced Networking and Applications, Vol 6, No 4 (2015), Pagination: 2414-2421Abstract
Wireless Sensor Networks (WSN) consist of a number of resource constrained sensors to collect and monitor data from unattended environments. Hence, security is a crucial task as the nodes are not provided with tamper-resistance hardware. Provision for secured communication in WSN is a challenging task especially due to the environment in which they are deployed. One of the main challenges is detection of intrusions. Intrusion detection system gathers and analyzes information from various areas within a computer or a network to identify possible security breaches. Different intrusion detection methods have been proposed in the literature to identify attacks in the network. Out of these detection methods, machine-learning based methods are observed to be efficient in terms of detection accuracy and alert generations for the system to act immediately. A brief study on different intrusions along with the machine learning based anomaly detection methods are reviewed in this work. The study also classifies the machine learning algorithms into supervised, unsupervised and semi-supervised learning-based anomaly detection. The performances of the algorithms are compared and efficient methods are identified.Keywords
Anomaly Detection, Intrusions, Intrusion Detection System, Machine-Learning Algorithms.Full Text
- Multi-Level Secret Sharing Scheme for Mobile Ad-Hoc Networks
Abstract Views :118 |
PDF Views:4
Authors
Affiliations
1 Department of Computer Science and Engineering, VNR VJIET, Hyderabad, IN
2 Sri Prakash College of Engineering, Tuni, IN
3 CRRao AIMSCS, University of Hyderabad Campus, Hyderabad, IN
1 Department of Computer Science and Engineering, VNR VJIET, Hyderabad, IN
2 Sri Prakash College of Engineering, Tuni, IN
3 CRRao AIMSCS, University of Hyderabad Campus, Hyderabad, IN
Source
International Journal of Advanced Networking and Applications, Vol 6, No 2 (2014), Pagination: 2253-2261Abstract
In this paper, we are concerned with security for Mobile Ad-hoc Networks (MANETs) using threshold cryptography. When we are applying cryptography to MANETs, key management schemes must provide the cryptographic keys in a secure manner and storing the secret information within the nodes, thwarting the activities of malicious nodes inside a network and is how to distribute the role of the trusted authority among the nodes. Mobile ad hoc networks (MANETs) represent complex distributed systems that comprise wireless mobile nodes that can freely and dynamically self-organize into arbitrary and temporary, ad-hoc network topologies. Secret Sharing Scheme is a method which distributes shares of a secret to a set of participants in such a way that only authorized subset of participants can uniquely reconstruct the secret and an unauthorized subset can get no information about the secret. In this paper we present a new multilevel secret sharing scheme by extending the Shamir's to the case that the global threshold is strictly greater than the sum of the compartment thresholds and we indicate how to use the threshold secret sharing schemes based on polynomial interpolation. These schemes are based on one-way functions (Discrete Logarithm) which are computationally perfect. In the first scheme the number of public shares grows exponentially with the number of participants. To overcome this disadvantage we proposed two efficient schemes in which the number of public shares ate linearly proportional to the number of participants. Both these schemes are similar except that in the third scheme the identities of the participants are also hidden. In this we also addressed the problem of malicious shareholders that aim to corrupt a secret sharing scheme. To prevent such a threat, legitimate shareholders must detect any modification of shares that has not been issued by a node responsible for the sharing of secret S.Keywords
Compartmented Access Structure, Computationally Perfect, Ideal, Secret Sharing Scheme, Verifiable, MANETs.Full Text
- A Study on Device Oriented Security Challenges in Internet of Things (IoT)
Abstract Views :174 |
PDF Views:6
Authors
Affiliations
1 Department of Computer Science, Avinashilingam University, Coimbatore-43, IN
1 Department of Computer Science, Avinashilingam University, Coimbatore-43, IN
Source
International Journal of Advanced Networking and Applications, Vol 8, No 5 (2017), Pagination: 3224-3231Abstract
Internet of Things (IoT) basically discusses about the connection of various physical devices through a network and let them take an active part by exchanging information through Internet. This paper presents important applications of IoT and the different challenges of IoT. Out of the various challenges, attacks on the devices used in IoT are of serious concern. Device oriented attacks and the defensive mechanisms are studied in this paper. A comparison is done for the specific malicious attacks on the M2M communicating devices.
Keywords
Applications, Challenges, Device Oriented Security Challenges, M2M Communicating Devices, Security Solutions.Full Text
References
- OvidiuVermason, Peter Friess From Research and Innovation to Market Deployment(River publishers series in communications, pg.39-61, 2014).
- Karen Rose, Scott Eldridge, Lyman Chapin The Internet of Things-An Overview(pg. 20-43, October 2015).
- Alejandro González García, Manuel Álvarez Álvarez, Jordán Pascual Espada, Oscar Sanjuán Martínez, Juan Manuel Cueva Lovelle, Cristina Pelayo G-Bustelo Introduction to Devices Orchestration in Internet of Things Using SBPMN, International Journal of Artificial Intelligence and Interactive Multimedia,1( 4).
- White Paper on Machine-to-Machine Communication (M2M)http://tec.gov.in/pdf/Studypaper/White%20 Paper%20on%20 Machine-to-Machine%20(M2M) Communication.pdf
- Andrea Bartoli, Security Protocols Suite forMachinetoMachine Systems (UniversitatPolitècnica de Catalunya (UPC) pg. 24-29, Barcelona, April 2013).
- RobertEržen, Review of main security threats in Smart Home networks(Study programme: Information Communication Technology, pg.5-12, 2012)
- DeepaliVirmani, AnkitaSoni, ShringaricaChandel, ManasHemrajani Routing Attacks in Wireless Sensor Networks-A Survey (BhagwanParshuram Institue of Technology, India).
- Development of Total Quality Engineering Education Model Using QFD
Abstract Views :186 |
PDF Views:0
Authors
Affiliations
1 Dept. of Mechanical Engg., Cramster Educational Services Pvt. Ltd. , Visakhaptnam, IN
2 Government Poly Technic, Vizianagaram, IN
3 Government Poly Technic, Bhimili, Visakhapatnam Dist, IN
4 Department of Mechanical Engineering, Andhra University, Visakhapatnam, IN
1 Dept. of Mechanical Engg., Cramster Educational Services Pvt. Ltd. , Visakhaptnam, IN
2 Government Poly Technic, Vizianagaram, IN
3 Government Poly Technic, Bhimili, Visakhapatnam Dist, IN
4 Department of Mechanical Engineering, Andhra University, Visakhapatnam, IN
Source
Journal of Engineering Education Transformations, Vol 21, No 4 (2008), Pagination: 1-6Abstract
The development and socio-economic condition of a nation is determined by enhancing the quality in Engineering education. There is a greater need for high quality education to produce technically skilled and creative man-power in India.- Outlier Detection in Secure Shell Honeypot using Particle Swarm Optimization Technique
Abstract Views :154 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science, SRMV College of Arts and Science, Coimbatore-20, IN
2 Department of Computer Applications, SRMV College of Arts and Science, Coimbatore-20, IN
3 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women University, Coimbatore-43, IN
1 Department of Computer Science, SRMV College of Arts and Science, Coimbatore-20, IN
2 Department of Computer Applications, SRMV College of Arts and Science, Coimbatore-20, IN
3 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women University, Coimbatore-43, IN
Source
International Journal of Advanced Networking and Applications, Vol 9, No 3 (2017), Pagination: 3443-3450Abstract
With trends and technologies, developments and deployments, network communication has become vital and inevitable with human beings. On the other side, a network communication without security is powerless. There are so many technologies and developments have been ischolar_mained to provide a secure and an efficient means of communication through network. Parallel to this, network threats and attacks are also trendy and much technologized. In order to detect such a kind of threats and attacks, this research work proposes honeypot technology. Honeypot is a supplemented active defense system for network security. It traps attacks, records intrusion information about tools and activities of the hacking process, and prevents attacks outbound from the compromised system. This research work implements a kind of honeypot called Secure Shell (SSH) honeypot. SSH honeypot is a secure communication channel which allows users to remotely control computer systems. With the implementation of SSH honeypot, this research work collects the incoming and outgoing traffic data in a network. The collected traffic data can be then analyzed to detect outliers in order to find the abnormal or malicious traffic. This research work detects outliers from the collected SSH honeypot data using Particle Swarm Optimization technique which belongs to the category of cluster-based outlier detection method. With experiments and results, Particle Swarm Optimization shows best results in detecting outliers and has best cost function when compared to other cluster-based algorithms like Genetic Algorithm and Differential Evolution algorithm.Keywords
Differential Evolution, Genetic Algorithm, Honeypots, Particle Swarm Optimization, Secure Shell.Full Text
References
- Feng Zhang, Shijie Zhou. Zhiguang Qin, Jinde Liu, Honeypot: A Supplemented Active Defense System for Network Security, IEEE, 2003, 231-235.
- Ioannis Koniaris, Georgios Papadimitriou, Petros Nicopolitidis, Mohammad Obaidat, Honeypots Deployment for the Analysis and Visualization of Malware Activity and Malicious Connections, IEEE, 2014, 1825-1830.
- Aaditya Jain, Dr. Bala Buksh, Advance Trends in Network Security with Honeypot and its Comparative Study with other Techniques, International Journal of Engineering Trends and Technology, 29, 2015, 304-312.
- Shaik Bhanu, Girish Khilari, Varun Kumar, Analysis of SSH attacks of Darknet using Honeypots, International Journal of Engineering Development and Research, 3, 2014, 348- 350.
- Abdallah Ghourabi, Adel Bouhoula, Data Analyzer Based on Data Mining for Honeypot Router, IEEE, 2015, 1-7.
- Ren Hui Gong, Mohammad Zulkernine, Purang Abolmaesumi, A Software Implementation of a Genetic Algorithm Based Approach to Network Intrusion Detection, IEEE, 2005, 1-5.
- Adam Slowik, Application of an Adaptive Differential Evolution Algorithm with Multiple Trial Vectors to Artificial Neural Network Training, IEEE, 58, 2011, 3160-3167.
- Russell C. Eberhart, Yuhui Shi, Particle Swarm Optimization: Developments, Applications and Resources, IEEE, 2001, 81-86.
- Enrique Alba and Marco Tomassini, Parallelism and Evolutionary Algorithms, IEEE, 6, 2002, 443462.
- P. Garcı´a-Teodoro, J. Dı´az-Verdejo, G. Macia´Ferna´ndez, E. Va´zquez, Anomaly-Based Network Intrusion Detection: Techniques, Systems and Challenges, Elsevier, 2009, 18-28.
- Roshan Chitrakar, Huang Chuanhe, Anomaly based Intrusion Detection using Hybrid Learning Approach of Combining k-Medoids Clustering and Naïve Bayes Classification, IEEE, 2015, 1-5.
- Robin Berthier, Michel Cukier, Profiling Attacker Behaviour Following SSH Compromises, IEEE, 2007, 1-7.
- A. M. Riad, Ibrahim Elhenawy, Ahmed Hassan and Nancy Awadallah, Visualize Network Anomaly Detection by Using K-Means Clustering Algorithm, International Journal of Computer Networks & Communications (IJCNC), 5, 2013, 195-208.
- Naila Belhadj Aissa, Mohamed Guerroumi, SemiSupervised Statistical Approach for Network Anomaly Detection, Elsevier, 2016, 1090 – 1095.
- Amandeep Singh, Navdeep Singh, Review of Implementing a Working Honeypot System, International Journal of Advanced Research in Computer Science and Software Engineering, 3(6), 2013, 1007-1011.
- Comparison of RSA-Threshold Cryptography and ECC-Threshold Cryptography for Small Mobile Adhoc Networks
Abstract Views :118 |
PDF Views:0
Authors
G. Padmavathi
1,
B. Lavanya
1
Affiliations
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore-641043, IN
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore-641043, IN
Source
International Journal of Advanced Networking and Applications, Vol 3, No 4 (2012), Pagination: 1245-1252Abstract
A mobile ad hoc network is a special type of wireless network in which a collection of mobile hosts with wireless network interfaces may form a temporary network. Without the aid of proper fixed infrastructure, providing secure communications is a big challenge. The strength of the security solutions very much depends on the cryptographic keys used for communication. Efficient key management is an important requirement of such networks. For networks like MANET which are basically constrained networks with minimum resources, identification of suitable asymmetric cryptosystem is a vital one. Hence an attempt has been made in this paper to identity a suitable asymmetric-threshold based cryptosystems for small MANETs. The study focuses on the comparison of Rivest Shamir Adelman-Threshold Cryptography and Elliptic Curve Cryptography Threshold Cryptography in terms of the performance parameters like key generation time, Encryption time, Decryption time and communication cost. Different small network scenarios with variable node sizes and key sizes are experimented and the results show that ECC-TC is the most desirable asymmetric-threshold cryptosystem for small MANET.Keywords
MANET, Threshold Cryptography, Elliptic Curve Cryptography, RSA.Full Text
- SPIM Architecture for MVC Based Web Applications
Abstract Views :119 |
PDF Views:0
Authors
Affiliations
1 Department of MCA, New Horizon College of Engineering, Bangalore-560087, IN
2 Department of Computer Science, Avinashilingam University for Women, Coimbatore-641047, IN
3 School of Physics, Madurai Kamaraj University, Madurai-625021, IN
4 Lakshmi Systems, Madurai-625020, IN
1 Department of MCA, New Horizon College of Engineering, Bangalore-560087, IN
2 Department of Computer Science, Avinashilingam University for Women, Coimbatore-641047, IN
3 School of Physics, Madurai Kamaraj University, Madurai-625021, IN
4 Lakshmi Systems, Madurai-625020, IN
Source
International Journal of Advanced Networking and Applications, Vol 1, No 1 (2009), Pagination: 63-68Abstract
The Model/View/Controller design pattern divides an application environment into three components to handle the user-interactions, computations and output respectively. This separation greatly favors architectural reusability. The pattern works well in the case of single-address space and not proven to be efficient for web applications involving multiple address spaces. Web applications force the designers to decide which of the components of the pattern are to be partitioned between the server and client(s) before the design phase commences. For any rapidly growing web application, it is very difficult to incorporate future changes in policies related to partitioning. One solution to this problem is to duplicate the Model and controller components at both server and client(s). However, this may add further problems like delayed data fetch, security and scalability issues. In order to overcome this, a new architecture SPIM has been proposed that deals with the partitioning problem in an alternative way. SPIM shows tremendous improvements in performance when compared with a similar architecture.Keywords
Design Pattern, Model/View/Controller, Partitioning, SOA, Web Application.Full Text
- Investigation of Deep Learning Optimizers for False Window Size Injection Attack Detection in Unmanned Aerial Vehicle Network Architecture
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Authors
N. Vanitha
1,
G. Padmavathi
1
Affiliations
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, IN
1 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, IN
Source
ICTACT Journal on Communication Technology, Vol 12, No 3 (2021), Pagination: 2465-2470Abstract
The Unmanned Aerial Vehicle (UAV) network plays a prominent role in this pandemic era. Nowadays UAVs are applied in various applications like military, civil etc. This article works on the Search and Rescue application part. UAV networks are applied in search and rescue operations in order to find the missing people in Hill areas. Due to false data dissemination attacks some UAVs in the network will lost the data so the rescue will become an issue. In order to detect those attacks this work uses Feed Forward Neural network with back propagation algorithm. This work experiments chosen optimizers to get the accurate detection of attack and compares the results among the optimizers All the more explicitly this examination did in the Delay- Tolerant based Decentralized Multi-Layer UAV ad-hoc organization Assisting VANET (DDMUAV) design utilizing Opportunistic Network Environment (ONE) test system.Keywords
Unmanned Aerial Vehicle, Delay Tolerant, Neural Network, Optimizer, Simulation.References
- Alireza Abbaspour, Kang K. Yen, Shirin Noei and Arman Sargolzaei, “Detection of Fault Data Injection Attack on UAV Using Adaptive Neural Network”, Procedia Computer Science, Vol. 95, pp. 193-200, 2016.
- A. Alsarhan, A.R. Al-Ghuwairi and I.T. Almalkawi, “Machine Learning-Driven Optimization for Intrusion Detection in Smart Vehicular Networks”, Wireless Personal Communications, Vol. 117, pp. 3129-3152, 2021.
- F. Nordemann and R. Tonjes, “Transparent and Autonomous Store-Carry-Forward Communication in Delay Tolerant Networks (DTNs)”, Proceedings of International Conference on Computing, Networking and Communications, pp. 761-765, 2012.
- A. Shukla, G. Kalnoor and A. Kumar, “Improved Recognition Rate of Different Material Category using Convolutional Neural Networks”, Materials Today: Proceedings, pp. 1-7, 2021.
- H. Sedjelmaci, S. M. Senouci and N. Ansari, “A Hierarchical Detection and Response System to Enhance Security Against Lethal Cyber-Attacks in UAV Networks”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 48, No. 9, pp. 1594-1606, 2018.
- V. Chang, B. Gobinathan and S. Kannan, “Automatic Detection of Cyberbullying using Multi-Feature based Artificial Intelligence with Deep Decision Tree Classification”, Computers and Electrical Engineering, Vol. 92, pp. 1-18, 2021.
- Ilker Bekmezci, Ozgur Koray,Sahingoz and Samil Temel, “Flying Ad-Hoc Networks (FANETs): A Survey”, Ad-Hoc Networks, Vol. 1, pp. 1254-1270, 2013.
- T. Karthikeyan, K. Praghash and K.H. Reddy, “Binary Flower Pollination (BFP) Approach to Handle the Dynamic Networking Conditions to Deliver Uninterrupted Connectivity”, Wireless Personal Communications, Vol. 117, pp. 1-20, 2021.
- M.J. Kang and J.W. Kang, “Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security”, PLoS ONE, Vol. 11, No. 6, pp. 1-14, 2016.
- Alan Kim, B. Wampler and H. Aldridge, “Cyber Attack Vulnerabilities Analysis for Unmanned Aerial Vehicles”, Infotech Aerospace, pp. 1-12, 2012.
- Kuldeep Singh and Karandeep Singh, “A Survey and Analysis of Mobility Models in Mobile Adhoc Network”, International Journal of Advances in Electronics and Computer Science, Vol. 2, No. 1, pp. 29-33, 2015.
- S. Misra, B.K. Saha nd S. Pal, “A Developer’s Guide to the ONE Simulator. In: Opportunistic Mobile Networks”, Proceedings of International Conference on Computer Communications and Networks, pp. 53-88, 2016.
- S. Kitada, G. Hirakawa, G. Sato, N. Uchida and Y. Shibata, “DTN Based MANET for Disaster Information Transport by Smart Devices”, Proceedings of International Conference on Network-Based Information Systems, pp. 26-31, 2015.
- Sixiao Wei, Linqiang Ge, Wei Yu, Genshe Chen, Khanh Pham, Erik Blasch, Dan Shen and Chao Lu, “Simulation study of Unmanned Aerial Vehicle Communication Networks Addressing Bandwidth Disruptions”, Proceedings of International Conference on Sensors and Systems for Space Applications, pp. 1-8, 2014.
- Stephen George, “FAA Unmanned Aircraft Systems (UAS) Cyber Security Initiatives”, Federal Aviation Administration, pp. 1-19, 2015.
- Yi Zhou, Nan Cheng, Ning Lu, and Xuemin Shen, “Multi-UAV-Aided Networks: Aerial-Ground Cooperative Vehicular Networking Architecture”, IEEE Vehicular Technology Magazine, Vol. 10, No. 4, pp. 36-44, 2015.
- Yirui Wu, Dabao Wei and Jun Feng, “Network Attacks Detection Methods Based on Deep Learning Techniques: A Survey”, Security and Communication Networks, Vol. 2020, pp. 1-18, 2020.
- N. Vanitha and G. Padmavathi, “A Study on Various Cyber-Attacks and their Classification in UAV Assisted Vehicular Ad-Hoc Networks”, Proceedings of International Conference on Computational Intelligence, Cyber Security and Computational Models, pp. 1-13, 2018.
- N. Vanitha and P. Ganapathi, “Traffic Analysis of UAV Networks Using Enhanced Deep Feed Forward Neural Networks (EDFFNN)”, Proceedings of International Conference on Research on Machine and Deep Learning Applications for Cyber Security, pp. 219-244, 2020.