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Padmavathi, G.
- 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.- 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.- 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.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).
- 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.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.- 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