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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MobFuzz: Adaptive Multi-objective Optimization in Gray-box Fuzzing

Gen Zhang (National University of Defense Technology), Pengfei Wang (National University of Defense Technology), Tai Yue (National University of Defense Technology), Xiangdong Kong (National University of Defense Technology), Shan Huang (National University of Defense Technology), Xu Zhou (National University of Defense Technology), Kai Lu (National University of Defense Technology)

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WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

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The Taming of the Stack: Isolating Stack Data from...

Kaiming Huang (Penn State University), Yongzhe Huang (Penn State University), Mathias Payer (EPFL), Zhiyun Qian (UC Riverside), Jack Sampson (Penn State University), Gang Tan (Penn State University), Trent Jaeger (Penn State University)

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PHYjacking: Physical Input Hijacking for Zero-Permission Authorization Attacks on...

Xianbo Wang (The Chinese University of Hong Kong), Shangcheng Shi (The Chinese University of Hong Kong), Yikang Chen (The Chinese University of Hong Kong), Wing Cheong Lau (The Chinese University of Hong Kong)

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