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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)
  • Validity and Reliability of the Scale Internet Users’ Information Privacy Concerns (IUIPC)
    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), and Romain Rouvoy (Univ. Lille / Inria)

    • Issue 3

  • Exploring Mental Models of the Right to Informational Self-Determination of Office Workers in Germany
    Jan Tolsdorf (Hochschule Bonn-Rhein-Sieg University of Applied Sciences), Florian Dehling (Hochschule Bonn-Rhein-Sieg University of Applied Sciences), Delphine Reinhardt (University of Göttingen), and Luigi Lo Iacono (Hochschule Bonn-Rhein-Sieg University of Applied Sciences)
  • Genome Reconstruction Attacks Against Genomic Data-Sharing Beacons
    Kerem Ayoz (Bilkent University), Erman Ayday (Case Western Reserve University), and Ercument Cicek (Bilkent University)
  • The Motivated Can Encrypt (Even with PGP)
    Glencora Borradaile (Oregon State University), Kelsy Kretschmer (Oregon State University), Michele Gretes (Stand), and Alexandria LeClerc (Oregon State University)
  • Three Years Later: A Study of MAC Address Randomization In Mobile Devices And When It Succeeds
    Ellis Fenske (US Naval Academy), Dane Brown (US Naval Academy), Jeremy Martin (MITRE), Travis Mayberry (US Naval Academy), Peter Ryan, Jr. (MITRE), and Erik Rye (CMAND)
  • SoK: Privacy-Preserving Collaborative Tree-based Model Learning
    Sylvain Chatel (EPFL), Apostolos Pyrgelis (EPFL), Juan Ramón Troncoso-Pastoriza (EPFL), and Jean-Pierre Hubaux (EPFL)
  • FoggySight: A Scheme for Facial Lookup Privacy
    Ivan Evtimov (University of Washington), Pascal Sturmfels (University of Washington), and Tadayoshi Kohno (University of Washington)
  • Who Can Find My Devices? Security and Privacy of Apple's Crowd-Sourced Bluetooth Location Tracking System
    Milan Stute (Technical University of Darmstadt), Alexander Heinrich (Technical University of Darmstadt), Tim Kornhuber (Technical University of Darmstadt), and Matthias Hollick (Technical University of Darmstadt)
  • Faster homomorphic comparison operations for BGV and BFV
    Ilia Iliashenko (imec-COSIC, KU Leuven, Belgium) and Vincent Zucca (Équipe DALI, Université de Perpignan via Domitia, France; LIRMM, UMR 5506, Université de Montpellier, CNRS, France)
  • Foundations of Ring Sampling
    Viktoria Ronge (Friedrich-Alexander University Erlangen-Nuremberg), Christoph Egger (Friedrich-Alexander University Erlangen-Nuremberg), Russell W. F. Lai (Friedrich-Alexander University Erlangen-Nuremberg), Dominique Schröder (Friedrich-Alexander University Erlangen-Nuremberg), and Hoover H. F. Yin (The Chinese University of Hong Kong)
  • Fast Privacy-Preserving Punch Cards
    Saba Eskandarian (Stanford University)
  • Awareness, Adoption, and Misconceptions of Web Privacy Tools
    Peter Story (Carnegie Mellon University), Daniel Smullen (Carnegie Mellon University), Yaxing Yao (Carnegie Mellon University), Alessandro Acquisti (Carnegie Mellon University), Lorrie Faith Cranor (Carnegie Mellon University), Norman Sadeh (Carnegie Mellon University), and Florian Schaub (University of Michigan)
  • The Role of Privacy in Digitalization – Analyzing Perspectives of German Farmers
    Sebastian Linsner (Technical University of Darmstadt), Franz Kuntke (Technical University of Darmstadt), Enno Steinbrink (Technical University of Darmstadt), Jonas Franken (Technical University of Darmstadt), Christian Reuter (Technical University of Darmstadt), and Sebastian Linsner (Technical University of Darmstadt)
  • Data Portability between Online Services: An Empirical Analysis on the Effectiveness of GDPR Art. 20
    Emmanuel Syrmoudis (Technical University of Munich), Stefan Mager (Ludwig-Maximilians-University of Munich), Sophie Kuebler-Wachendorff (Ludwig-Maximilians-University of Munich), Paul Pizzinini (Ludwig-Maximilians-University of Munich), Jens Grossklags (Technical University of Munich), and Johann Kranz (Ludwig-Maximilians-University of Munich)
  • Digital inequality through the lens of self-disclosure
    Jooyoung Lee (The Pennsylvania State University), Sarah Rajtmajer (The Pennsylvania State University), Eesha Srivatsavaya (The Pennsylvania State University), and Shomir Wilson (The Pennsylvania State University)
  • The CNAME of the Game: Large-scale Analysis of DNS-based Tracking Evasion
    Yana Dimova (imec-DistriNet, KU Leuven), Gunes Acar (imec-COSIC, KU Leuven), Lukasz Olejnik (European Data Protection Supervisor), Wouter Joosen (imec-DistriNet, KU Leuven), and Tom Van Goethem (imec-DistriNet, KU Leuven)
  • DNA Sequencing Flow Cells and the Security of the Molecular-Digital Interface
    Peter Ney (University of Washington), Lee Organick (University of Washington), Jeff Nivala (University of Washington), Luis Ceze (University of Washington), and Tadayoshi Kohno (University of Washington)
  • A First Look at Private Communications in Video Games using Visual Features
    Abdul Wajid (SEECS, NUST), Nasir Kamal (SEECS, NUST), Muhammad Sharjeel (SEECS, NUST), Raaez Muhammad Sheikh (SEECS, NUST), Huzaifah Bin Wasim (SEECS, NUST), Muhammad Hashir Ali (SEECS, NUST), Wajahat Hussain (SEECS, NUST), Syed Taha Ali (SEECS, NUST), and Latif Anjum (SEECS, NUST)
  • ML-CB: Machine Learning Canvas Block
    Nathan Reitinger (UMD) and Michelle L. Mazurek (UMD)
  • Defining Privacy: How Users Interpret Technical Terms in Privacy Policies
    Jenny Tang (Wellesley College), Hannah Shoemaker (Pomona College), Ada Lerner (Wellesley College), and Eleanor Birrell (Pomona College)
  • Unlinkable Updatable Hiding Databases and Privacy-Preserving Loyalty Programs
    Aditya Damodaran (University of Luxembourg) and Alfredo Rial (University of Luxembourg)
  • Growing synthetic data through differentially-private vine copulas
    Sébastien Gambs (UQAM), Frédéric Ladouceur (Ericsson), Antoine Laurent (UQAM), and Alexandre Roy-Gaumond (UQAM)
  • privGAN: Protecting GANs from membership inference attacks at low cost to utility
    Sumit Mukherjee (Microsoft), Yixi Xu (Microsoft), Anusua Trivedi (Microsoft), Nabajyoti Patowary (Microsoft), Juan Lavista Ferres (Microsoft)
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