PhyCloak: Obfuscating Sensing from Communication Signals

Speaker/Bio

Bowen Song is a Master of Science student at Boston University, ECE department. He is currently studying set and string reconciliation under the guidance of Professor Trachtenberg and has research interests in the related field.

Abstract

Recognition of human activities and gestures using pre-existing WiFi signals has been shown to be feasible in recent studies. Given the pervasiveness of WiFi signals, this emerging sort of sensing poses a serious privacy threat. This paper is the first to counter the threat of unwanted or even malicious communication based sensing: it proposes a blackbox sensor obfuscation technique PhyCloak which distorts only the physical information in the communication signal that leaks privacy. The data in the communication signal is preserved and, in fact, the throughput of the link is increased with careful design. Moreover, the design allows coupling of the PhyCloak module with legitimate sensors, so that their sensing is preserved, while that of illegitimate sensors is obfuscated. The effectiveness of the design is validated via a prototype implementation on an SDR platform. [1]

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