Combating jamming attacks in multi-channel IoT networks using game theory
Author | Guizani, Mohsen |
Author | Gouissem, A. |
Author | Abualsaud, K. |
Author | Yaacoub, E. |
Author | Khattab, T. |
Available date | 2022-12-14T10:07:34Z |
Publication Date | 2020-03-01 |
Publication Name | Proceedings - 3rd International Conference on Information and Computer Technologies, ICICT 2020 |
Identifier | http://dx.doi.org/10.1109/ICICT50521.2020.00081 |
Citation | Guizani, M., Gouissem, A., Abualsaud, K., Yaacoub, E., & Khattab, T. (2020, March). Combating jamming attacks in multi-channel IoT networks using game theory. In 2020 3rd International Conference on Information and Computer Technologies (ICICT) (pp. 469-474). IEEE. |
ISBN | 9781728172835 |
Abstract | Jamming attacks are among the most widely used techniques to block and disturb legitimate communications. Several techniques are used in the literature to combat these attacks. However, most of them either require the increase in transmission power or the implementation of complex coordination schemes which are not feasible in limited resources Internet of Things (IoT) devices. Therefore, in this paper, a defending strategy against jamming attacks is designed for health monitoring IoT networks with multiple Orthogonal frequency-division multiplexing (OFDM) slow fading channels. In particular, minimizing the worst case jamming effect on the IoT sensors communications is modeled as a Colonel Blotto game. By analyzing the Nash Equilibrium (NE) of the game, an anti-jamming power allocating strategy is proposed and is shown to be effective in combating jamming attacks without the need for extra power and resources. |
Sponsor | This publication was made possible by the NPRP award [NPRP 10-1205-160012] from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors. |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | Game theory Jamming attacks Multi channel IoT networks |
Type | Conference Paper |
Pagination | 469-474 |
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Computer Science & Engineering [2284 items ]