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Accepted papers for PETS 2021

Issue 1

Note: These papers are not yet suitable for citation. Page numbers may change in the final papers.

  • SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications
    A K M Mubashwir Alam (Wright State University), Sagar Sharma (), and Keke Chen (Wright State University)
  • Controlled Functional Encryption Revisited: Multi-Authority Extensions and Efficient Schemes for Quadratic Functions
    Miguel Ambrona (NTT Secure Platform Laboratories), Dario Fiore (IMDEA Software Institute), and Claudio Soriente (NEC Laboratories Europe)
  • Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning
    Valentino Rizzo (Ermes Cyber Security SRL), Stefano Traverso (Ermes Cyber Security SRL), and Marco Mellia (Politecnico di Torino)
  • Differential Privacy at Risk: Bridging Randomness and Privacy Budget
    Ashish Dandekar (École Normale Supériure, Paris, France), Debabrota Basu (Chalmers University of Technology, Gothenberg, Sweden), Stéphane Bressan (National University of Singapore, Singapore), and Ashish Dandekar (École Normale Supérieure)
  • On the (Im)Practicality of Adversarial Perturbation for Image Privacy
    Arezoo Rajabi (Oregon State University), Rakesh B. Bobba (Oregon State University), Mike Rosulek (Oregon State University), Charles V. Wright (Portland State University), and Wu-chi Feng (Portland State University)
  • SoK: Privacy-Preserving Reputation Systems
    Stan Gurtler (University of Waterloo) and Ian Goldberg (University of Waterloo)
  • Scaling up Differentially Private Deep Learning with Fast Per-Example Gradient Clipping
    Jaewoo Lee (University of Georgia) and Daniel Kifer (Penn State University)
  • Real-time Analysis of Privacy-(un)aware IoT Applications
    Leonardo Babun (Florida International University), Z. Berkay Celik (Purdue University), Patrick McDaniel (Pennsylvania Sate University), and A. Selcuk Uluagac (Florida International University)
  • Secure Training of Decision Trees with Continuous Attributes
    Mark Abspoel (CWI, The Netherlands), Daniel Escudero (Aarhus University, Denmark), and Nikolaj Volgushev (Pleo Technologies ApS)
  • Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning
    Sameer Wagh (Princeton University), Shruti Tople (Microsoft Research), Fabrice Benhamouda (Algorand Foundation), Eyal Kushilevitz (Technion), Prateek Mittal (Princeton University), and Tal Rabin (Algorand Foundation)
  • The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services
    Yuantian Miao (Swinburne University of Technology), Minhui Xue (The University of Adelaide), Chao Chen (Swinburne University of Technology), Lei Pan (Deakin University), Jun Zhang (Swinburne University of Technology), Benjamin Zi Hao Zhao (The University of New South Wales and CSIRO-Data61), Dali Kaafar (Macquarie University and CSIRO-Data61), and Yang Xiang (Swinburne University of Technology)
  • SoK: Managing Longitudinal Privacy of Publicly Shared Personal Online Data
    Theodor Schnitzler (Ruhr-Universität Bochum), Shujaat Mirza (Courant Institute of Mathematical Sciences, New York University), Markus Dürmuth (Ruhr-Universität Bochum), and Christina Pöpper (New York University Abu Dhabi)
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