Ioanna Tzialla (New York University), Abhiram Kothapalli (Carnegie Mellon University), Bryan Parno (Carnegie Mellon University), Srinath Setty (Microsoft Research)

This paper introduces Verdict, a transparency dictionary, where an untrusted service maintains a label-value map that clients can query and update (foundational infrastructure for end-to-end encryption and other applications). To prevent unauthorized modifications to the dictionary, for example, by a malicious or a compromised service provider, Verdict produces publicly-verifiable cryptographic proofs that it correctly executes both reads and authorized updates. A key advance over prior work is that Verdict produces efficiently-verifiable proofs while incurring modest proving overheads. Verdict accomplishes this by composing indexed Merkle trees (a new SNARK-friendly data structure) with Phalanx (a new SNARK that supports amortized constant-sized proofs and leverages particular workload characteristics to speed up the prover). Our experimental evaluation demonstrates that Verdict scales to dictionaries with millions of labels while imposing modest overheads on the service and clients.

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HARPO: Learning to Subvert Online Behavioral Advertising

Jiang Zhang (University of Southern California), Konstantinos Psounis (University of Southern California), Muhammad Haroon (University of California, Davis), Zubair Shafiq (University of California, Davis)

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SemperFi: Anti-spoofing GPS Receiver for UAVs

Harshad Sathaye (Northeastern University), Gerald LaMountain (Northeastern University), Pau Closas (Northeastern University), Aanjhan Ranganathan (Northeastern University)

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Detecting Obfuscated Function Clones in Binaries using Machine Learning

Michael Pucher (University of Vienna), Christian Kudera (SBA Research), Georg Merzdovnik (SBA Research)

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Demo #15: Remote Adversarial Attack on Automated Lane Centering

Yulong Cao (University of Michigan), Yanan Guo (University of Pittsburgh), Takami Sato (UC Irvine), Qi Alfred Chen (UC Irvine), Z. Morley Mao (University of Michigan) and Yueqiang Cheng (NIO)

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