Giuseppe Ateniese (Stevens Institute of Technology), Long Chen (New Jersey Institute of Technology), Mohammard Etemad (Stevens Institute of Technology), Qiang Tang (New Jersey Institute of Technology)

A high-quality outsourced storage service is crucial for many existing applications. For example, hospitals and data centers need to guarantee the availability of their systems to perform routine daily activities. Such a system should protect users against downtime and ensure data availability over time. Continuous data availability is a critical property to measure the quality of an outsourced storage service, which implies that outsourced data is continuously available to the server during the entire storage period. We formally study the Proof of Storage-Time (PoSt), the notion initially proposed in the Filecoin whitepaper, which enables a verifier to audit the continuous data availability of an outsourced storage service. We provide a formal security model of PoSt and generic constructions that are proven secure under our definition. Moreover, our concrete instantiation can yield a PoSt protocol with an extremely efficient verification: a single hash computation to verify a proof of size around 200 bits. This makes our scheme applicable even in the decentralized storage marketplace enabled by blockchain.

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FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

Thijs van Ede (University of Twente), Riccardo Bortolameotti (Bitdefender), Andrea Continella (UC Santa Barbara), Jingjing Ren (Northeastern University), Daniel J. Dubois (Northeastern University), Martina Lindorfer (TU Wien), David Choffnes (Northeastern University), Maarten van Steen (University of Twente), Andreas Peter (University of Twente)

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SurfingAttack: Interactive Hidden Attack on Voice Assistants Using Ultrasonic...

Qiben Yan (Michigan State University), Kehai Liu (Chinese Academy of Sciences), Qin Zhou (University of Nebraska-Lincoln), Hanqing Guo (Michigan State University), Ning Zhang (Washington University in St. Louis)

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BLAG: Improving the Accuracy of Blacklists

Sivaramakrishnan Ramanathan (University of Southern California/Information Sciences Institute), Jelena Mirkovic (University of Southern California/Information Sciences Institute), Minlan Yu (Harvard University)

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DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing

Yue Duan (Cornell University), Xuezixiang Li (UC Riverside), Jinghan Wang (UC Riverside), Heng Yin (UC Riverside)

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