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)