DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-HOC NETWORKS USING SELF-ORGANIZING TEMPORAL NEURAL NETWORKS

James Cannady

Abstract

Mobile ad hoc networks continue to be a difficult environment for effective intrusion detection. In an effort to achieve reliable distributed attack detection in a resource-efficient manner a self-organizing neural network-based intrusion detection system was developed. The approach, Distributed Self-organizing Intrusion Response (DISIR), enables real-time detection in a decentralized manner that demonstrates a distributed analysis functionality which facilitates the detection of complex attacks against MANETs. The results of the evaluation of the approach and a discussion of additional areas of research is presented.

References

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Paper Citation


in Harvard Style

Cannady J. (2010). DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-HOC NETWORKS USING SELF-ORGANIZING TEMPORAL NEURAL NETWORKS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 229-234. DOI: 10.5220/0002712802290234


in Bibtex Style

@conference{icaart10,
author={James Cannady},
title={DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-HOC NETWORKS USING SELF-ORGANIZING TEMPORAL NEURAL NETWORKS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={229-234},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002712802290234},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - DETECTION OF DISTRIBUTED ATTACKS IN MOBILE AD-HOC NETWORKS USING SELF-ORGANIZING TEMPORAL NEURAL NETWORKS
SN - 978-989-674-021-4
AU - Cannady J.
PY - 2010
SP - 229
EP - 234
DO - 10.5220/0002712802290234