Reduced complexity intrusion detection in sensor networks using genetic algorithm

Rahul Khanna, Huaping Liu, Hsiao Hwa Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

We propose a reduced-complexity genetic algorithm for intrusion detection of resource constrained multi-hop mobile sensor networks. Traditional intrusion detection mechanisms have limited applicability to the sensor networks due to scarce battery and processing resources. Therefore, an effective scheme would require a power efficient and lightweight approach to identify malicious attacks. The goal of this paper is to evaluate sensor node attributes by measuring the perceived threat and its suitability to host local monitoring node (LMN) that acts as trusted proxy agent for the sink and capable of securely monitoring its neighbors. Security attributes in conjunction with genetic algorithm jointly optimizes the placement of monitoring nodes (i.e., LMN) by dynamically evaluating node fitness by profiling workloads patterns, packet statistics, utilization data, battery status, and quality-of-service compliance.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Conference on Communications, ICC 2009
DOIs
Publication statusPublished - 2009 Nov 19
Event2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
Duration: 2009 Jun 142009 Jun 18

Publication series

NameIEEE International Conference on Communications
ISSN (Print)0536-1486

Other

Other2009 IEEE International Conference on Communications, ICC 2009
CountryGermany
CityDresden
Period09-06-1409-06-18

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Reduced complexity intrusion detection in sensor networks using genetic algorithm'. Together they form a unique fingerprint.

Cite this