"Protecting your daily in-home activity information from a wireless snooping attack," by Vijay Srinivasan, John Stankovic, and Kamin Whitehouse:
Abstract: In this paper, we first present a new privacy leak in residential wireless ubiquitous computing systems, and then we propose guidelines for designing future systems to prevent this problem. We show that we can observe private activities in the home such as cooking, showering, toileting, and sleeping by eavesdropping on the wireless transmissions of sensors in a home, even when all of the transmissions are encrypted. We call this the Fingerprint and Timing-based Snooping (FATS) attack. This attack can already be carried out on millions of homes today, and may become more important as ubiquitous computing environments such as smart homes and assisted living facilities become more prevalent. In this paper, we demonstrate and evaluate the FATS attack on eight different homes containing wireless sensors. We also propose and evaluate a set of privacy preserving design guidelines for future wireless ubiquitous systems and show how these guidelines can be used in a hybrid fashion to prevent against the FATS attack with low implementation costs.The group was able to infer surprisingly detailed activity information about the residents, including when they were home or away, when they were awake or sleeping, and when they were performing activities such as showering or cooking. They were able to infer all this without any knowledge of the location, semantics, or source identifier of the wireless sensors, while assuming perfect encryption of the data and source identifiers.