ABSTRACT

In privacy research on radiofrequency-based protocols, the dominant focus has remained on Bluetooth, WiFi, and Zigbee, while a broader and arguably more consequential attack surface has gone largely unnoticed: the privacy risks created by the composition of everyday wireless protocols. Widely deployed systems such as
KeeLoq remotes, vehicle TPMS sensors, and other sub-GHz devices continuously emit metadata and timing structure that, when analyzed jointly rather than in isolation, enable powerful behavioral inference. This work-in-progress paper argues that privacy leakage in these environments is not merely a property of individual protocols, but an emergent property of their interaction, correlation, and composition across devices, spaces, and routines. The resulting attack surface arises both from protocol metadata that directly degrades privacy and from the latent relationships between devices and the ways users move among and interact with them over time. We present preliminary evidence that these composed signals expose underappreciated opportunities for inference and tracking, and we outline a research agenda for characterizing and mitigating this broader class of privacy failures

BIOS

Sergey Bratus is the Dartmouth College Distinguished Professor in Cyber Security, Technology, and Society and an Associate Professor of Computer Science. In 2018--2024 he served as a Program Manager at DARPA's Information Innovation Office (I2O), where he created multiple fundamental research programs in cybersecurity, resilience, and sustainment of critical software.

Larry Hernandez is a PhD student at Dartmouth, joining academia after over a decade of industry experience. Previously he participated as principal investigator in the DARPA Cyber Fast Track program, contributed to the NSA SELinux project, and performed reverse engineering and security assessments for customers in finance, IT and defense. Current research focus is the science of reverse engineering and rapid software-hardware understanding.