Xiaokuan Zhang (The Ohio State University), Jihun Hamm (The Ohio State University), Michael K. Reiter (University of North Carolina at Chapel Hill), Yinqian Zhang (The Ohio State University)

Machine learning empowers traffic-analysis attacks that breach users' privacy from their encrypted traffic. Recent advances in deep learning drastically escalate such threats.
One prominent example demonstrated recently is a traffic-analysis attack against video streaming by using convolutional neural networks. In this paper, we explore the adaption of techniques previously used in the domains of adversarial machine learning and differential privacy to mitigate the machine-learning-powered analysis of streaming traffic.

Our findings are twofold. First, constructing adversarial samples effectively confounds an adversary with a predetermined classifier but is less effective when the adversary can adapt to the defense by using alternative classifiers or training the classifier with adversarial samples. Second, differential-privacy guarantees are very effective against such statistical-inference-based traffic analysis, while remaining agnostic to the machine learning classifiers used by the adversary. We propose two mechanisms for enforcing differential privacy for encrypted streaming traffic, and evaluate their security and utility. Our empirical implementation and evaluation suggest that the proposed statistical privacy approaches are promising solutions in the underlying scenarios.

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OBFUSCURO: A Commodity Obfuscation Engine on Intel SGX

Adil Ahmad (Purdue), Byunggill Joe (KAIST), Yuan Xiao (Ohio State University), Yinqian Zhang (Ohio State University), Insik Shin (KAIST), Byoungyoung Lee (Purdue/SNU)

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Measurement and Analysis of Hajime, a Peer-to-peer IoT Botnet

Stephen Herwig (University of Maryland), Katura Harvey (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), George Hughey (University of Maryland), Richard Roberts (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), Dave Levin (University of Maryland)

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SANCTUARY: ARMing TrustZone with User-space Enclaves

Ferdinand Brasser (Technische Universität Darmstadt), David Gens (Technische Universität Darmstadt), Patrick Jauernig (Technische Universität Darmstadt), Ahmad-Reza Sadeghi (Technische Universität Darmstadt), Emmanuel Stapf (Technische Universität Darmstadt)

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Private Continual Release of Real-Valued Data Streams

Victor Perrier (Data61, CSIRO and ISAE-SUPAERO), Hassan Jameel Asghar (Macquarie University and Data61, CSIRO), Dali Kaafar (Macquarie University and Data61, CSIRO)

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