Malicious Relay Detection Using Sentinels: A Stochastic Geometry Framework

Utku Tefek, Anshoo Tandon, and Teng Joon Lim



Abstract :Next generation wireless networks are under high riskof security attacks due to increased connectivity and informationsharing among peer nodes. Some of the nodes could potentially bemalicious, intending to disrupt or tamper sensitive data transfer inthe network. In this paper, we present a detailed analysis of the sentinelbased data integrity attack detection of malicious relays usinga stochastic geometry framework. We assume a practical channelmodel for each wireless link and apply a stochastic geometry approachto interference modeling. Two detection schemes dependingon the level of connectivity between sentinel devices are proposed:isolated and co-operative detection. For both schemes, attackdetection probability is derived as a function of important networkparameters, and the minimum density of sentinels to achievea given detection probability is calculated. It will be shown that areasonable attack detection probability can be achieved even whenthe sentinel node density is much lower than the relay node density.​ 

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