Traffic Inference in Anonymous MANETs

Abstract—The open wireless medium in a mobile ad-hoc net-work (MANET) enables malicious traffic analysis to dynamically infer the network traffic pattern in hostile environments. The disclosure of the traffic pattern and its changes is often devas-tating in a mission-critical MANET. A number of anonymous routing protocols have been recently proposed as an effective countermeasure against traffic analysis in MANETs. In this paper, we propose a novel traffic inference algorithm, called TIA, which enables a passive global adversary to accurately infer the traffic pattern in an anonymous MANET without compromising any node. As the first work of its kind, TIA works on existing on-demand anonymous MANET routing protocols. Detailed simulations show that TIA can infer the traffic pattern with an accuracy as high as 95%. Our results in this paper highlight the necessity for cross-layer designs to defend a MANET against traffic analysis. I