A. Damodaram

Work place: JNTU College of Engineering, Hyderabad, India

E-mail: damodarama@rediffmail.com


Research Interests: Computational Science and Engineering, Software Engineering, Computer Networks, Image Processing, Data Mining, Data Structures and Algorithms


Avula Damodaram obtained his B. Tech degree in CSE in 1989, M. Tech in CSE in 1995 and PhD in Computer science in 2000 all from JNTUH, Hyderabad. His areas of interest are Computer Networks Software engineering, Data Mining and Image Processing. He has successfully guided 8 PhD and 2 MS scholars apart from myriad M. Tech projects. He is currently guiding 9 scholars for PhD and 1 scholar for MS.

He is on the editorial board of 2 International Journals and a number of course materials. He has organized as many as 30 workshops, short term courses and other refresher and orientation programs. He has published 35 research papers in National and International Journals and also presented 45 papers at National and International conferences. On the basis of his scholarly achievements and other multifarious services, he was honored with the award of DISTINGUISHED ACADAMICIAN by Pentagram Research Center, India, in January 2010. He was also awarded as the Best Professor for the year 2013 by the government of Andhra Pradesh, 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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Blactr: A Technique to Revoke the Misbehaving Users with TTP

By H.Jayasree A. Damodaram

DOI: https://doi.org/10.5815/ijcnis.2013.01.08, Pub. Date: 8 Jan. 2013

Anonymous credential systems permit the users to authenticate themselves in a privacy-preserving way. An anonymous credential system is of major practical relevance because it is the best means of providing privacy for users. In this paper, we propose a technique known as Blacklistable Anonymous Credentials with Trust Reputation (BLACTR) for revoking misbehaving users with Trusted Third Party (TTP). The technique uses both Certifying Authority (CA) review as well as other user reviews in order to blacklist a user making use of the fuzzy and rule matched to check if the person is to be blacklisted or not. The proposed technique performed well when compared to BLAC and BLACR.

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Other Articles