Detecting Route Attraction Attacks in Wireless Networks

Selecting high performance routes in wireless networks requires the exchange of link quality information among nodes. Adversaries can manipulate this functionality by advertising fake qualities for links; by doing so, they can attract routes and subsequently launch pernicious attacks. Our measurements suggest that malicious route attraction can fatally impact throughput. We design a framework that is effective against both independent and colluding attackers. In the latter case, we consider both local and remote colluders. With local collusion, malicious nodes exchange and advertise fake routing information to increase the probability of being selected as relays. Remote collusion refers to nodes residing in distant parts of the network that (i) create sybil identities in a local neighborhood and / or (ii) utilize link quality reports to advertise fake links. Our framework combines packet signing and frequency hopping to accurately detect the adversaries. We implement the framework on our testbed and conduct experiments to assess its efficacy. We observe that our framework provides significant throughput benefits by detecting attackers with 90% accuracy.