Today people increasingly have the opportunity to opt-in to "usage-based" automotive insurance programs for reducing insurance premiums. In these programs, participants install devices in their vehicles that monitor their driving behavior, which raises some privacy concerns. Some devices collect fine-grained speed data to monitor driving habits. Companies that use these devices claim that their approach is privacy-preserving because speedometer measurements do not have physical locations. However, we show that with knowledge of the user's home location, as the insurance companies have, speed data is sufficient to discover driving routes and destinations when trip data is collected over a period of weeks. To demonstrate the real-world applicability of our approach we applied our algorithm, elastic pathing, to data collected over hundreds of driving trips occurring over several months. With this data and our approach, we were able to predict trip destinations to within 250 meters of ground truth in 10 of the traces and within 500 meters in 20 of the traces. This result, combined with the amount of speed data that is being collected by insurance companies, constitutes a substantial breach of privacy because a person's regular driving pattern can be deduced with repeated examples of the same paths with just a few weeks of monitoring.
We analyze three new consumer electronic gadgets in order to gauge the privacy and security trends in mass-market UbiComp devices. Our study of the Slingbox Pro uncovers a new information leakage vector for encrypted streaming multimedia. By exploiting properties of variable bitrate encoding schemes, we show that a passive adversary can determine with high probability the movie that a user is watching via her Slingbox, even when the Slingbox uses encryption. We experimentally evaluated our method against a database of over 100 hours of network traces for 26 distinct movies. Despite an opportunity to provide significantly more location privacy than existing devices, like RFIDs, we find that an attacker can trivially exploit the Nike+iPod Sport Kit's design to track users; we demonstrate this with a GoogleMaps-based distributed surveillance system. We also uncover security issues with the way Microsoft Zunes manage their social relationships. We show how these products' designers could have significantly raised the bar against some of our attacks. We also use some of our attacks to motivate fundamental security and privacy challenges for future UbiComp devices.