Malicious Relay Detection Using Sentinels: A Stochastic Geometry Framework

Utku Tefek, Anshoo Tandon, and Teng Joon Lim

109 303.303-315

10.1109/JCN.2020.000010

Abstract :Next generation wireless networks are under high risk of security attacks due to increased connectivity and information sharing among peer nodes. Some of the nodes could potentially be malicious, intending to disrupt or tamper sensitive data transfer in the network. In this paper, we present a detailed analysis of the sentinel based data integrity attack detection of malicious relays using a stochastic geometry framework. We assume a practical channel model for each wireless link and apply a stochastic geometry approach to interference modeling. Two detection schemes depending on the level of connectivity between sentinel devices are proposed: isolated and co-operative detection. For both schemes, attack detection probability is derived as a function of important network parameters, and the minimum density of sentinels to achieve a given detection probability is calculated. It will be shown that a reasonable attack detection probability can be achieved even when the sentinel node density is much lower than the relay node density.

Index terms :Attack detection, internet-of-things, sentinel, stochastic geometry