International Journal of Advanced Networking and Applications

3411-3420

Authors: Patel Rinkuben N., Dr. Nirav V. Bhatt

Networking is a trending research area where the various research took place. Diversified filed of the Network is Sensor Network, which is a centrally adopted due to features and flexibility of sensors. Various disciplines like a military, medical, forest, Industries, Health monitoring and more, where WSN is established. Sensors have various pitfalls like limited lifetime and Storage, installed in misanthropic environments. Frequently power up or replace an energy source is a crucial task. Data communication in WSN is possible in the MAC layer. MAC is responsible for node schedule and sensing task. Collision and retransmission also lead to waste of energy. Variety of MAC protocols are developed for various qualities of service factors like energy, latency, reliability, delay, jitter, etc., however, none of them are given a satisfactory result for various QoS parameters. To overcome some of the pitfalls we need to achieve various QoS parameters. In this Research MAC is designed with a priority mechanism over clusters. Data with the highest priority are sent without or with a very negligible amount of delay. Higher priority packets are transmitted before a no prioritized packet. Using various priorities, the node energy, low delay and high throughput are achieved over standard MAC Protocols.

3428-3431

Authors: Atul Chaturvedi, Manoj Kumar Misra, Varun Shukla, Neelam Srivastava, S.P.Tripathi

The available key agreement schemes using number theoretic, elliptic curves etc are common for cryptanalysts and associated security is vulnerable. This vulnerability further increases when we talk about modern efficient computers. So there is a need of providing new mechanism for key agreement with different properties so intruders get surprised and communication scenarios becomes stronger than before. In this paper, we propose a key agreement protocol which works in a non commutative group. We prove that our protocol meets the desired security attributes under the assumption that Conjugacy Search Problem and Decomposition Problem are hard in non commutative groups.

3443-3450

Authors: M.Sithara, M.Chandran, G.Padmavathi

With trends and technologies, developments and deployments, network communication has become vital and in evitable with human beings. On the other side, a network communication without security is powerless. There are so many technologies and developments have been rooted 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.

3455-3460

Authors: Manas Kumar Yogi, L. Yamuna

This paper is intended to introduce an efficient as well as robust training mechanism for a neural network which can be used for testing the functionality of software. The traditional setup of neural network architecture is used constituting the two phases -training phase and evaluation phase. The input test cases are to be trained in first phase and consequently they behave like normal test cases to predict the output as untrained test cases. The test oracle measures the deviation between the outputs of untrained test cases with trained test cases and authorizes a final decision. Our framework can be applied to systems where number of test cases outnumbers the functionalities or the system under test is too complex. It can also be applied to the test case development when the modules of a system become tedious after modification.