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We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function evaluation (SFE) which enables two parties to jointly compute a function without disclosing their private inputs.
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Privacy-preserving outsourced calculation on floating point numbers
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Efficient Server-Aided 2PC for Mobile Phones. In PoPETs
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I am Robot: (Deep) Learning to Break Semantic Image CAPTCHAs. In IEEE EuroS&P
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Optimized Honest-Majority MPC for Malicious Adversaries - Breaking the 1 Billion-Gate Per Second Barrier. In IEEE S&P
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Privacy-Preserving Classification on Deep Neural Network
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EzPC: Programmable, Efficient, and Scalable Secure Two-Party Computation
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PICS: Private Image Classification with SVM
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SecureML: A System for Scalable Privacy-Preserving Machine Learning.. In IEEE S&P
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