Affiliation:
1. Augusta University, and University of California, Irvine
2. University of California, Irvine
Abstract
This article focuses on the new privacy challenges that arise in smart homes. Specifically, the article focuses on inferring the user’s activities—which may, in turn, lead to the user’s privacy—via inferences through device activities and network traffic analysis. We develop techniques that are based on a cryptographically secure token circulation in a ring network consisting of smart home devices to prevent inferences from device activities, via
device workflow
, i.e., inferences from a coordinated sequence of devices’ actuation. The solution hides the device activity and corresponding channel activities, thus preserving the individual’s activities. We also extend our solution to deal with a large number of devices and devices that produce large-sized data by implementing parallel rings. Our experiments also evaluate the performance in terms of communication overheads of the proposed approach and the obtained privacy.
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction
Cited by
1 articles.
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1. Classification of Encrypted IoT Traffic despite Padding and Shaping;Proceedings of the 21st Workshop on Privacy in the Electronic Society;2022-11-07