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An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks

Abdollahi, Mostafa; Malekinasab, Kousar; Tu, Wanqing; Bag-Mohammadi, Mozafar

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Authors

Mostafa Abdollahi

Kousar Malekinasab

Mozafar Bag-Mohammadi



Contributors

Lyes Khoukhi
Editor

Sharief Oteafy
Editor

Eyuphan Bulut
Editor

Abstract

An active jammer could severely degrade the communication quality for wireless networks. Since all wireless nodes openly access the shared media, the harsh effects are exaggerated by retransmission attempts of affected devices. Fast and precise detection of the jammer is of vital importance for heterogeneous wireless environments such as the Internet of things (IoT). It could activate a series of corrective countermeasures to ensure the robust operation of the network. In this paper, we propose a local, straightforward, and numerical metric called the number of jammed slots (NJS), by which we can quickly detect the presence of a jammer and identify the jammed nodes at the software level in broadcast networks. NJS calculation is carried out by a central node which collects the MAC-layer statuses of all wireless nodes in a periodical fashion. Our simulation results indicate that NJS outperforms current detection methods in terms of accuracy and precision.

Citation

Abdollahi, M., Malekinasab, K., Tu, W., & Bag-Mohammadi, M. (2021). An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks. In L. Khoukhi, S. Oteafy, & E. Bulut (Eds.), Proceedings of the IEEE 46th Conference on Local Computer Networks (LCN 2021) (209-216). https://doi.org/10.1109/lcn52139.2021.9524936

Conference Name 2021 IEEE 46th Conference on Local Computer Networks (LCN)
Publication Date 2021
Deposit Date Oct 27, 2021
Publicly Available Date Oct 27, 2021
Publisher Institute of Electrical and Electronics Engineers
Pages 209-216
Book Title Proceedings of the IEEE 46th Conference on Local Computer Networks (LCN 2021)
DOI https://doi.org/10.1109/lcn52139.2021.9524936
Public URL https://durham-repository.worktribe.com/output/1139604

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