Accepted papers for PETS 2021

Issue 1

  • 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)
  • Issue 2

  • Automated Extraction and Presentation of Data Practices in Privacy Policies
    Duc Bui (University of Michigan), Kang G. Shin (University of Michigan), Jongmin Choi (Samsung Research), and Jun Bum Shin (Samsung Research)
  • Scalable Privacy-Preserving Distributed Learning
    David Froelicher (EPFL), Juan R. Troncoso-pastoriza (EPFL), Apostolos Pyrgelis (EPFL), Sinem Sav (EPFL), Joao Sa Sousa (EPFL), Jean-Philippe Bossuat (EPFL), and Jean-Pierre Hubaux (EPFL)
  • Face-Off: Adversarial Face Obfuscation
    Varun Chandrasekaran (University of Wisconsin-Madison), Chuhan Gao (Microsoft), Brian Tang (University of Wisconsin-Madison), Kassem Fawaz (University of Wisconsin-Madison), Somesh Jha (University of Wisconsin-Madison), and Suman Banerjee (University of Wisconsin-Madison)
  • Privacy-Preserving Multiple Tensor Factorization for Synthesizing Large-Scale Location Traces with Cluster-Specific Features
    Takao Murakami (AIST), Koki Hamada (NTT), Yusuke Kawamoto (AIST), and Takuma Hatano (NSSOL)
  • "Warn Them" or "Just Block Them"?: Comparing Privacy Concerns of Older and Working Age Adults
    Hirak Ray (University of Maryland, Baltimore County), Flynn Wolf (University of Maryland, Baltimore County), Ravi Kuber (University of Maryland, Baltimore County), and Adam J. Aviv (The George Washington University)
  • Website Fingerprinting in the Age of QUIC
    Jean-Pierre Smith (ETH Zurich), Adrian Perrig (ETH Zurich), and Prateek Mittal (Princeton)
  • EL PASSO: Efficient and Lightweight Privacy-preserving Single Sign On
    Zhiyi Zhang (UCLA), Michał Król (City, University of London), Alberto Sonnino (UCL), Lixia Zhang (UCLA), and Etienne Riviere (UCLouvain)
  • Efficient homomorphic evaluation of k-NN classifiers
    Martin Zuber (CEA, LIST) and Renaud Sirdey (CEA, LIST)
  • Defending Against Microphone-Based Attacks with Personalized Noise
    Yuchen Liu (Indiana University Bloomington), Ziyu Xiang (Indiana University Bloomington), EJ Seong (Indiana University Bloomington), Apu Kapadia (Indiana University Bloomington), and Donald Williamson (Indiana University Bloomington)
  • Holes in the Geofence: Privacy Vulnerabilities in "Smart" DNS Services
    Rahel A. Fainchtein (Georgetown University), Adam A. Aviv (The George Washington University), Micah Sherr (Georgetown University), Stephen Ribaudo (Georgetown University), and Armaan Khullar (Georgetown University)
  • Too Close for Comfort: Morasses of (Anti-) Censorship in the Era of CDNs
    Devashish Gosain (IIIT Delhi), Mayank Mohindra (IIIT Delhi), and Sambuddho Chakravarty (IIIT Delhi)
  • Privacy-Preserving & Incrementally-Deployable Support for Certificate Transparency in Tor
    Rasmus Dahlberg (Karlstad University), Tobias Pulls (Karlstad University), Tom Ritter (Mozilla), and Paul Syverson (U.S. Naval Research Laboratory)
  • DyPS: Dynamic, Private and Secure GWAS
    Túlio Pascoal (SnT, University of Luxembourg), Jérémie Decouchant (SnT, University of Luxembourg), Antoine Boutet (Insa-Lyon, CITI, Inria), and Paulo Esteves-Verissimo (SnT, University of Luxembourg)
  • Revisiting the Factor Structure of IUIPC-10
    Thomas Gross (Newcastle University)
  • A calculus of tracking: theory and practice
    Giorgio Di Tizio (University of Trento) and Fabio Massacci (University of Trento)
  • "Did you know this camera tracks your mood?": Modeling People's Privacy Expectations and Preferences in the Age of Video Analytics
    Shikun Zhang (Carnegie Mellon University), Yuanyuan Feng (Carnegie Mellon University), Lujo Bauer (Carnegie Mellon University), Lorrie Cranor (Carnegie Mellon University), Anupam Das (North Carolina State University), and Norman Sadeh (Carnegie Mellon University)
  • GANDaLF: GAN for Data-Limited Fingerprinting
    Se Eun Oh (University of Minnesota), Nate Mathews (Rochester Institute of Technology), Mohammad Saidur Rahman (Rochester Institute of Technology), Matthew Wright (Rochester Institute of Technology), and Nicholas Hopper (University of Minnesota)
  • Revisiting Membership Inference Under Realistic Assumptions
    Bargav Jayaraman (University of Virginia), Lingxiao Wang (University of California Los Angeles), Katherine Knipmeyer (University of Virginia), Quanquan Gu (University of California Los Angeles), and David Evans (University of Virginia)
  • Déjà vu: Abusing Browser Cache Headers to Identify and Track Online Users
    Vikas Mishra (Inria / Univ. Lille), Pierre Laperdrix (CNRS / Univ. Lille / Inria), Walter Rudametkin (Univ. Lille / Inria), Romain Rouvoy (Univ. Lille / Inria / IUF), and Romain Rouvoy (Univ. Lille / Inria)