Toward Efficient Solutions to Resist Mobile Traffic Sensors : How Much Performance Cost is Paid by On-demand Anonymous Routing Protocols ∗

The recent progress in embedded real-time system development has realized mobile traffic sensors, for example, embedded systems carried by palm-size Unmanned Aerial Vehicles (UAV). This has great impact on privacy design in mobile ad hoc networks because mobility introduces new privacy targets for the traffic sensors. In a mobile network, a node’s motion pattern, traffic pattern, standing venue and route-driven packet flows, and even the dynamic network topology, all become new interests of the mobile traffic sensors, bringing in new privacy challenges in addition to conventional identity privacy and message privacy. In particular, in wireless ad hoc networks mobile nodes must rely on ad hoc routing in communication. As the wireless medium is open to anyone within the transmission range, the baseline of the mobile traffic sensors is to exploit this routing opportunity to conduct various attacks threatening the network security and privacy. Recently, the on-demand routing approach has been used by several anonymous routing schemes to prevent mobile nodes from being traced by mobile traffic sensors[29]. In this paper we seek to compare the overhead incurred by security and anonymity operations of two recently proposed on-demand anonymous routing schemes, namely ANODR [28][27] (with an enhanced variant ASR [50]) and SDAR [8]. We use the standard on-demand scheme AODV [37] in the comparison to show how much overhead is paid by each anonymous on-demand scheme. Our simulation study shows that various design choices in anonymous routing trade performance with security protection. We conclude that extensive performance study is needed to evaluate the practicality of the existing and new anonymous routing schemes and their enhancements. Keywords—Performance study, Mobile traffic sensor, Anonymous routing, On demand routing Part of the work is funded by ONR MINUTEMAN grant N00014-01-C0016 and NSF NRT WHYNET grant ANI-0335302.

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