Accepted papers for PETS 2023
Issue 1
- Privacy Rarely Considered: Exploring Considerations in the Adoption of
Third-Party Services by Websites
Christine Utz (CISPA Helmholtz Center for Information Security), Sabrina Amft (CISPA Helmholtz Center for Information Security), Martin Degeling (Ruhr University Bochum), Thorsten Holz (CISPA Helmholtz Center for Information Security), Sascha Fahl (CISPA Helmholtz Center for Information Security), and Florian Schaub (University of Michigan) - Not Your Average App: A Large-scale Privacy Analysis of Android
Browsers
Amogh Pradeep (Northeastern University), Álvaro Feal (IMDEA Networks / Universidad Carlos III de Madrid), Julien Gamba (IMDEA Networks / Universidad Carlos III de Madrid), Ashwin Rao (University of Helsinki), Martina Lindorfer (TU Wien), Narseo Vallina-Rodriguez (IMDEA Networks / ICSI / AppCensus Inc.), and David Choffnes (Northeastern University) - “Revoked just now!” Users’ Behaviors Toward Fitness-Data Sharing with
Third-Party Applications
Noé Zufferey (University of Lausanne), Kavous Salehzadeh Niksirat (University of Lausanne), Mathias Humbert (University of Lausanne), and Kévin Huguenin (University of Lausanne) - SoK: Secure Aggregation based on cryptographic schemes for Federated
Learning
Mohamad Mansouri (EURECOM), Melek Önen (EURECOM), Wafa Ben Jaballah (Thales SIX GTS), and Mauro Conti (University of Padua) - Exploring Model Inversion Attacks in the Black-box Setting
Antreas Dionysiou (University of Cyprus), Vassilis Vassiliades (CYENS Centre of Excellence), and Elias Athanasopoulos (University of Cyprus) - No Privacy Among Spies: Assessing the Functionality and Insecurity of
Consumer Android Spyware Apps
Enze Liu (University of California, San Diego), Sumanth Rao (University of California, San Diego), Sam Havron (Meta), Grant Ho (University of California, San Diego), Stefan Savage (University of California, San Diego), Geoffrey M. Voelker (University of California, San Diego), and Damon McCoy (New York University) - Designing a Location Trace Anonymization Contest
Takao Murakami (AIST), Hiromi Arai (RIKEN), Koki Hamada (NTT), Takuma Hatano (NSSOL), Makoto Iguchi (Kii Corporation), Hiroaki Kikuchi (Meiji University), Atsushi Kuromasa (Data Society Alliance), Hiroshi Nakagawa (RIKEN), Yuichi Nakamura (SoftBank Corp.), Kenshiro Nishiyama (LegalForce), Ryo Nojima (NICT), Hidenobu Oguri (Fujitsu Limited), Chiemi Watanabe (Tsukuba University of Technology), Akira Yamada (KDDI Research, Inc.), Takayasu Yamaguchi (Akita Prefectural University), and Yuji Yamaoka (Fujitsu Limited) - Detect your fingerprint in your photographs : Photography-based
multi-feature Sybil detection
Yerim Kim (Korea University), Minjae Kim (Korea University), Myungjae Chung (Korea University), and Junbeom Hur (Korea University) - Identity Disentanglement for Anonymizing Faces
Minh-Ha Le (Linkoping University) and Niklas Carlsson (Linkoping University) - SoK: Secure E-Voting with Everlasting Privacy
Thomas Haines (Australian National University), Rafieh Mosaheb (University of Luxembourg), Johannes Mueller (University of Luxembourg), and Ivan Pryvalov (University of Luxembourg) - Investigating Privacy Decision-Making Processes Among Nigerian Men and
Women.
Victor Yisa (Dalhousie University), Reza Ghaiumy Anaraky (Clemson University), Bart P. Knijnenburg (Clemson University), and Rita Orji (Dalhousie University) - Privacy by Projection: Federated Population Density Estimation by
Projecting on Random Features
Zixiao Zong (University of California, Irvine), Mengwei Yang (University of California, Irvine), Justin Scott Ley (University of California, Irvine), Athina Markopoulou (University of California, Irvine), and Carter Butts (University of California, Irvine) - HeLayers: A Tile Tensors Framework for Large Neural Networks on
Encrypted Data
Ehud Aharoni (IBM Research - Haifa), Allon Adir (IBM Research - Haifa), Moran Baruch (IBM Research - Haifa and Bar Ilan University), Nir Drucker (IBM Research - Haifa), Gilad Ezov (IBM Research - Haifa), Ariel Farkash (IBM Research - Haifa), Lev Greenberg (IBM Research - Haifa), Ramy Masalha (IBM Research - Haifa), Guy Moshkowich (IBM Research - Haifa), Dov Murik (IBM Research - Haifa), Hayim Shaul (IBM Research - Haifa), and Omri Soceanu (IBM Research - Haifa) - Efficient decision tree training with new data structure for secure
multi-party computation
Koki Hamada (NTT), Dai Ikarashi (NTT), Ryo Kikuchi (NTT), and Koji Chida (Gunma University) - FrodoPIR: Simple, Scalable, Single-Server Private Information
Retrieval
Alex Davidson (Brave Software), Gonçalo Pestana (Brave Software), and Sofía Celi (Brave Software) - "Surprised, Shocked, Worried": User Reactions to Facebook Data
Collection from Third Parties
Patricia Arias-Cabarcos (Paderborn University), Saina Kjalili (unaffiliated), and Thorsten Strufe (KIT) - MIAShield: Defending Membership Inference Attacks via Preemptive
Exclusion of Members
Ismat Jarin (University of Michigan-Dearborn) and Birhanu Eshete (University of Michigan-Dearborn) - Dynamic Volume-Hiding Encrypted Multi-Maps with Applications to
Searchable Encryption
Ghous Amjad (Google), Sarvar Patel (Google), Giuseppe Persiano (University of Salerno), Kevin Yeo (Google), and Moti Yung (Google) - I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association
Studies
Túlio Pascoal (University of Luxembourg), Jérémie Decouchant (TU Delft), Antoine Boutet (INSA, INRIA, University of Lyon, CITI), and Marcus Völp (University of Luxembourg) - Is There a Reverse Privacy Paradox? An Exploratory Analysis of Gaps
Between Privacy Perspectives and Privacy-Seeking Behaviors
Jessica Colnago (Google), Alessandro Acquisti (Carnegie Mellon University), and Lorrie Cranor (Carnegie Mellon University) - Privacy Concerns and Acceptance Factors of OSINT for Cybersecurity: A
Representative Survey
Thea Riebe (TU Darmstadt, PEASEC), Tom Biselli (TU Darmstadt, PEASEC), Marc-André Kaufhold (TU Darmstadt, PEASEC), and Christian Reuter (TU Darmstadt, PEASEC) - Lox: Protecting the Social Graph in Bridge Distribution
Lindsey Tulloch (University of Waterloo) and Ian Goldberg (University of Waterloo) - How Much Privacy Does Federated Learning with Secure Aggregation
Guarantee?
Ahmed Roushdy Elkordy (University of Southern California), Jiang Zhang (University of Southern California), Yahya H. Ezzeldin (University of Southern California), Konstantinos Psounis (University of Southern California), and Salman Avestimehr (University of Southern California) - Private Multi-Winner Voting for Machine Learning
Adam Dziedzic (University of Toronto and Vector Institute), Christopher A. Choquette-Choo (Google Brain), Natalie Dullerud (University of Toronto and Vector Institute), Vinith Suriyakumar (MIT), Ali Shahin Shamsabadi (The Alan Turing Institute), Muhammad Ahmad Kaleem (University of Toronto and Vector Institute), Somesh Jha (University of Wisconsin), Nicolas Papernot (University of Toronto and Vector Institute), and Xiao Wang (Northwestern University) - Privacy-Aware Adversarial Network in Human Mobility Prediction
Yuting Zhan (Imperial College London), Hamed Haddadi (Imperial College London), and Afra Mashhadi (University of Washington) - Exploring privacy implications of awareness and control mechanisms in
smart home devices
Madiha Tabassum (University of North Carolina at Charlotte) and Heather Richter Lipford (University of North Carolina at Charlotte) - Dolphin: A Cellular Voice Based Internet Shutdown Resistance System
Piyush Kumar Sharma (IIIT Delhi), Rishi Sharma (IIIT Delhi), Kartikey Singh (IIIT Delhi), Mukulika Maity (IIIT Delhi), and Sambuddho Chakravarty (IIIT Delhi) - Multi-Party Replicated Secret Sharing over a Ring with Applications to
Privacy-Preserving Machine Learning
Alessandro Baccarini (University at Buffalo), Marina Blanton (University at Buffalo), and Chen Yuan (University at Buffalo) - Efficient Proofs of Software Exploitability for Real-world
Processors
Matthew Green (Johns Hopkins University), Mathias Hall-Andersen (Aarhus University), Eric Hennenfent (Trail of Bits), Gabriel Kaptchuk (Boston University), Benjamin Perez (Trail of Bits), and Gijs Van Laer (Johns Hopkins University) - On the Privacy Risks of Deploying Recurrent Neural Networks in Machine
Learning Models
Yunhao Yang (University of Texas at Austin), Parham Gohari (University of Texas at Austin), and Ufuk Topcu (University of Texas at Austin) - Blind My - Robust Stalking Prevention in Apple's Find My Network
Travis Mayberry (United States Naval Academy), Erik-Oliver Blass (Airbus), and Ellis Fenske (US Naval Academy) - Differentially Private Speaker Anonymization
Ali Shahin Shamsabadi (The Alan Turing Institute), Brij Mohan Lal Srivastava (INRIA), Aurélien Bellet (INRIA), Nathalie Vauquier (INRIA), Emmanuel Vincent (INRIA), Mohamed Maouche (INRIA), Marc Tommasi (INRIA), and Nicolas Papernot (University of Toronto and Vector Institute) - TWo-IN-one-SSE: Fast, Scalable and Storage-Efficient Searchable
Symmetric Encryption for Conjunctive and Disjunctive Boolean Queries
Arnab Bag (Indian Institute of Technology Kharagpur), Debadrita Talapatra (Indian Institute of Technology Kharagpur), Ayushi Rastogi (Indian Institute of Technology Kharagpur), Sikhar Patranabis (IBM Research India), and Debdeep Mukhopadhyay (Indian Institute of Technology Kharagpur) - Individualized PATE: Differentially Private Machine Learning with
Individual Privacy Guarantees
Franziska Boenisch (Free University Berlin), Christopher Mühl (Free University Berlin), Roy Rinberg (Columbia University), Jannis Ihrig (Free University Berlin), and Adam Dziedzic (University of Toronto and Vector Institute) - Understanding person identification via gait
Simon Hanisch (Technische Universität Dresden), Evelyn Muschter (Technische Universität Dresden), Adamantini Chatzipanagioti (Technische Universität Dresden), Shu-Chen Li (Technische Universität Dresden), and Thorsten Strufe (Karlsruhe Institute of Technology)
