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Evolving attackers against wireless sensor networks using genetic programming

Mrugala, K; Tuptuk, N; Hailes, S; (2017) Evolving attackers against wireless sensor networks using genetic programming. IET Wireless Sensor Systems , 7 (4) pp. 113-122. 10.1049/iet-wss.2016.0090. Green open access

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Abstract

Recent hardware developments have made it possible for the Internet of Things (IoT) to be built. A wide variety of industry sectors, including manufacturing, utilities, agriculture, transportation, and healthcare are actively seeking to incorporate IoT technologies in their operations. The increased connectivity and data sharing that give IoT systems their advantages also increase their vulnerability to attack. In this study, the authors explore the automated generation of attacks using genetic programming (GP), so that defences can be tested objectively in advance of deployment. In the authors' system, the GP-generated attackers targeted publish-subscribe communications within a wireless sensor networks that was protected by an artificial immune intrusion detection system (IDS) taken from the literature. The GP attackers successfully suppressed more legitimate messages than the hand-coded attack used originally to test the IDS, whilst reducing the likelihood of detection. Based on the results, it was possible to reconfigure the IDS to improve its performance. Whilst the experiments were focussed on establishing a proof-of-principle rather than a turnkey solution, they indicate that GP-generated attackers have the potential to improve the protection of systems with large attack surfaces, in a way that is complementary to traditional testing and certification.

Type: Article
Title: Evolving attackers against wireless sensor networks using genetic programming
Open access status: An open access version is available from UCL Discovery
DOI: 10.1049/iet-wss.2016.0090
Publisher version: http://dx.doi.org/10.1049/iet-wss.2016.0090
Language: English
Additional information: This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Keywords: Genetic algorithms, Internet of Things, security of data, telecommunication security, wireless sensor networks, wireless sensor network, genetic programming, Internet of Things, IoT technology, artificial immune intrusion detection system, artificial immune IDS
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/1566785
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