Title: A jamming detection method for multi-hop wireless networks based on association graph

Authors: Xianglin Wei; Qin Sun

Addresses: Nanjing Telecommunication Technology Research Institute, Nanjing 210007, China ' Nanjing Telecommunication Technology Research Institute, Nanjing 210007, China

Abstract: In this paper, a jamming detection algorithm based on association graph is put forward based on the observation that different jamming attacks will cause different network status changes in multi-hop wireless networks (MHWNs). The proposed algorithm consists of two phases, i.e., learning and detection phases. At the learning phase, different symptoms are extracted through learning from various samples collected in both jamming and jamming-free scenarios. Then, a symptom-attack association graph is built. At the detection phase, the association graph is adopted to detect the jamming attacks that lead to the observed symptoms. A series of simulation experiments on NS3 have validated that the proposed method can efficiently detect and classify typical jamming attacks, including reactive, random and constant jamming attacks.

Keywords: jamming attack; security; wireless network; association graph.

DOI: 10.1504/IJHPCN.2019.102128

International Journal of High Performance Computing and Networking, 2019 Vol.14 No.3, pp.284 - 293

Received: 23 Jun 2017
Accepted: 07 Nov 2017

Published online: 03 Sep 2019 *

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