Efforts to anonymize collections of location traces have often sought to reduce re-identification risks by dividing longer traces into multiple shorter, unlinkable segments. To ensure unlinkability, these algorithms delete parts from each location trace in areas where multiple traces converge, so that it is difficult to predict the movements of any one subject within this area and identify which follow-on trace segments belongs to the same subject. In this paper, we ask whether it is sufficient to base the definition of unlinkability on movement prediction models or whether the revealed trace segments themselves contain a fingerprint of the data subject that can be used to link segments and ultimately recover private information. To this end, we study a large set of vehicle locations traces collected through the Next Generation Simulation program. We first show that using vehicle moving characteristics related features, it is possible to identify outliers such as trucks or motorcycles from general passenger automobiles. We then show that even in a dataset containing similar passenger automobiles only, it is possible to use outlier driving behaviors to link a fraction of the vehicle trips. These results show that the definition of unlinkability may have to be extended for very precise location traces.

We present the boomerang protocol to efficiently retain information at a particular geographic location in a sparse network of highly mobile nodes without using infrastructure networks. To retain information around certain physical location, each mobile device passing that location will carry the information for a short while. This approach can become challenging for remote locations around which only few nodes pass by. To address this challenge, the boomerang protocol, similar to delay-tolerant communication, first allows a mobile node to carry packets away from their location of origin and periodically returns them to the anchor location. A unique feature of this protocol is that it records the geographical trajectory while moving away from the origin and exploits the recorded trajectory to optimize the return path. Simulations using automotive traffic traces for a southern New Jersey region show that the boomerang protocol improves packet return rate by 70 percent compared to a baseline shortest path routing protocol. This performance gain can become even more significant when the road map is less connected. Finally, we look at adaptive protocols that can return information within specified time limits.

We present the novel boomerang protocol to efficiently retain information at a particular geographic location in a sparse network of highly mobile nodes without use of infrastructure networks. Our proof-of-concept implementation revealed the main challenge in implementing the Boomerang protocol is to accurately detect whether a node is divergent from a recorded trajectory and then followed up with a detailed study to address the challenge. Simulation with automotive traffic traces for a southern New Jersey region shows that the protocol improves packet return rate by 70% compared to a baseline implementation using shortest path geographic routing.

Secure wireless communications typically rely on secret keys, which are hard to establish in a mobile setting without a key management infrastructure. In this paper, we propose a channel hopping protocol that lets two stations agree on a secret key over an open wireless channel and without use of any pre-existing key. It is secure against an adversary with typical consumer radio hardware that only allows receiving on a single (or a few) channel at a time. Theoretical analysis and simulation results indicate that this approach can generate a 128-bit key in 0.3 seconds. This is significantly faster than prior techniques that extract key material from the wireless channel.