Reinforcement-learning-based IDS for 6LoWPAN

Pasikhani, A.M. orcid.org/0000-0003-3181-4026, Clark, J.A. orcid.org/0000-0002-9230-9739 and Gope, P. orcid.org/0000-0003-2786-0273 (2022) Reinforcement-learning-based IDS for 6LoWPAN. In: 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom). 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 20-22 Oct 2021, Shenyang, China. Institute of Electrical and Electronics Engineers (IEEE) , pp. 1049-1060. ISBN 9781665416597

Abstract

The Routing Protocol for low power Lossy networks (RPL) is a critical operational component of low power wireless personal area networks using IPv6 (6LoWPANs). In this paper we propose a Reinforcement Learning (RL) based IDS to detect various attacks on RPL in 6LoWPANs, including several un-addressed by current research. The proposed scheme can also detect previously unseen attacks and the presence of mobile intruders. The scheme is well suited to the resource constrained environments of our target networks.

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Authors/Creators:	Pasikhani, A.M. https://orcid.org/0000-0003-3181-4026 Clark, J.A. https://orcid.org/0000-0002-9230-9739 Gope, P. https://orcid.org/0000-0003-2786-0273
Copyright, Publisher and Additional Information:	© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords:	IDS; Reinforcement-Learning; RPL-attack; Machine Learning; RPL; 6LoWPAN
Dates:	Published (online): 9 March 2022 Published: 9 March 2022
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User:	Symplectic Sheffield
Date Deposited:	16 Feb 2024 11:29
Last Modified:	17 Feb 2024 00:42
Status:	Published
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Refereed:	Yes
Identification Number:	https://doi.org/10.1109/trustcom53373.2021.00144
Related URLs:	Author

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Reinforcement-learning-based IDS for 6LoWPAN

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