Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

Sevil Şen; John Clark; Juan Tapiador

Ad Hoc Networks. First International Conference, ADHOCNETS 2009, Niagara Falls, Ontario, Canada, September 22-25, 2009. Revised Selected Papers

Research Article

Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

Download

469 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-11723-7_15,
    author={Sevil Şen and John Clark and Juan Tapiador},
    title={Power-Aware Intrusion Detection in Mobile Ad Hoc Networks},
    proceedings={Ad Hoc Networks. First International Conference, ADHOCNETS 2009, Niagara Falls, Ontario, Canada, September 22-25, 2009. Revised Selected Papers},
    proceedings_a={ADHOCNETS},
    year={2012},
    month={7},
    keywords={Mobile ad hoc networks intrusion detection power-aware evolutionary computation genetic programming multi-objective optimization},
    doi={10.1007/978-3-642-11723-7_15}
}

Sevil Şen
John Clark
Juan Tapiador
Year: 2012
Power-Aware Intrusion Detection in Mobile Ad Hoc Networks
ADHOCNETS
Springer
DOI: 10.1007/978-3-642-11723-7_15

Sevil Şen¹^,*, John Clark¹^,*, Juan Tapiador¹^,*

1: University of York

*Contact email: ssen@cs.york.ac.uk, jac@cs.york.ac.uk, jet@cs.york.ac.uk

Abstract

Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

Keywords: Mobile ad hoc networks intrusion detection power-aware evolutionary computation genetic programming multi-objective optimization

Published: 2012-07-05

: http://dx.doi.org/10.1007/978-3-642-11723-7_15