Proceedings of the 2018 Workshop on IoT Security and Privacy 2018
DOI: 10.1145/3229565.3229567
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Abstract: The number and variety of Internet-connected devices have grown enormously in the past few years, presenting new challenges to security and privacy. Research has shown that network adversaries can use traffic rate metadata from consumer IoT devices to infer sensitive user activities. Shaping traffic flows to fit distributions independent of user activities can protect privacy, but this approach has seen little adoption due to required developer effort and overhead bandwidth costs. Here, we present a Python li…

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