S. Mamatha

Work place: Bhoj Reddy Engineering College for Women, Hyderabad, India

E-mail: msathineni@yahoo.co.in

Website:

Research Interests: Computer Networks, Network Architecture, Network Security

Biography

S. Mamatha obtained her B.E in CSE from O.U in 1998 and M. Tech in CSE from JNTUH in 2004. She is pursuing Ph.D in CSE from JNTUH, Hyderabad. She is working as Associate Professor in Bhoj Reddy Engineering College for Women and has 15yrs of teaching experience. Her areas of interest include security in wired and wireless Networks. Ms. Mamatha is a life member of ISTE, India.

Author Articles
Enhanced Intrusion Detection System for Malicious Node Detection in Mobile Ad hoc Networks using Data Transmission Quality of Nodes

By S. Mamatha A. Damodaram

DOI: https://doi.org/10.5815/ijcnis.2014.10.04, Pub. Date: 8 Sep. 2014

Mobile Ad hoc NETworks (MANETs) are the new generation of networks that offer unrestricted mobility without any underlying infrastructure. It relies on the cooperation of all the participating nodes. Due to their open nature and lack of infrastructure, security for MANETS has become an intricate problem than the security in other networks. The conventional security mechanisms of protecting a wired network are not sufficient for these networks. Hence a second level of defense to detect and respond to the security problem called an Intrusion detection system is required. Generally the malicious nodes demonstrate a different behavioral pattern of all the other normal nodes. So an Intrusion Detection System based on anomaly based intrusion detection that works by checking the behavior of the nodes was proposed. Here, in this paper to determine the behavior of the nodes as malicious or legitimate a Data Transmission Quality (DTQ) function is used. The DTQ function is defined in such a way that it will be close to a constant or keep changing smoothly for genuine nodes and will keep on diminishing for malicious nodes.. The final decision of confirming nodes as malicious is determined by a group consensus method. The evaluation results show that the proposed method increases the detection rate as well as decreases the false positive rate.

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