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)
Issue 2
Some of these papers are accepted conditionally on approval of a shepherd.
- Intersectional Thinking about PETs: A Study of Library Privacy
Nora McDonald (George Mason University), Rachel Greenstadt (New York University), and Andrea Forte (Drexel University) - Heads in the Clouds? Measuring Universities’ Migration to Public Clouds: Implications for Privacy & Academic Freedom
Tobias Fiebig (Max-Planck-Institut für Informatik), Seda Gürses (TU Delft), Carlos H. Gañán (TU Delft), Erna Kotkamp (TU Delft), Fernando Kuipers (TU Delft), Martina Lindorfer (TU Wien), Menghua Prisse (TU Delft), and Taritha Sari (TU Delft) - Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry
Gonzalo Munilla Garrido (Technical University of Munich), Xiaoyuan Liu (UC Berkeley), Florian Matthes (Technical University of Munich), and Dawn Song (UC Berkeley) - Privacy Property Graph: Towards Automated Privacy Threat Modeling via Static Graph-based Analysis
Immanuel Kunz (Fraunhofer AISEC), Konrad Weiss (Fraunhofer AISEC), Christian Banse (Fraunhofer AISEC), and Angelika Schneider (Fraunhofer AISEC) - DeepSE-WF: Unified Security Estimation for Website Fingerprinting Defenses
Alexander Veicht (ETH Zürich), Cedric Renggli (University of Zurich), and Diogo Barradas (University of Waterloo) - iPET: Privacy Enhancing Traffic Perturbations for Secure IoT Communications
Akshaye Shenoi (TUMCREATE Singapore), Prasanna Karthik Vairam (National University of Singapore), Kanav Sabharwal (National University of Singapore), Li Jialin (National University of Singapore), and Dinil Mon Divakaran (Acronis Research) - Creative beyond TikToks: Investigating Adolescents’ Social Privacy Management on TikTok
Nico Ebert (ZHAW School of Management and Law), Tim Geppert (ZHAW School of Management and Law), Joanna Strycharz (University of Amsterdam), Melanie Knieps (University of Zurich), Michael Hönig (ZHAW School of Management and Law), and Elke Brucker-Kley (ZHAW School of Management and Law) - Distributed GAN-Based Privacy-Preserving Publication of Vertically-Partitioned Data
Xue Jiang (Technical University of Munich), Yufei Zhang (Technical University of Munich), Xuebing Zhou (Huawei Technologies Deutschland GmbH), and Jens Grossklags (Technical University of Munich) - How Website Owners Face Privacy Issues: Thematic Analysis of Responses from a Covert Notification Study Reveals Diverse Circumstances and Challenges
Alina Stöver (TU Darmstadt), Nina Gerber (TU Darmstadt), Henning Pridöhl (Universität Bamberg), Max Maass (), Sebastian Bretthauer (Goethe-Universität Frankfurt), Indra Spiecker (Goethe-Universität Frankfurt), Matthias Hollick (TU Darmstadt), and Dominik Herrmann (Universität Bamberg) - Opting Out from Web Tracking with Global Privacy Control
Sebastian Zimmeck (Wesleyan University), Oliver Wang (Wesleyan University), Kuba Alicki (Wesleyan University), Jocelyn Wang (Wesleyan University), and Sophie Eng (Wesleyan University) - Watching your call: Breaking VoLTE Privacy in LTE/5G Networks
Zishuai Cheng (Beijing University of Posts and Telecommunications), Mihai Ordean (University of Birmingham), Flavio D. Garcia (University of Birmingham), Baojiang Cui (Beijing University of Posts and Telecommunications), and Dominik Rys (University of Birmingham) - Strengthening Privacy-Preserving Record Linkage using Diffusion
Frederik Armknecht (University of Mannheim), Youzhe Heng (University of Mannheim), and Rainer Schnell (University of Duisburg-Essen) - A Unified Framework for Quantifying Privacy Risk in Synthetic Data
Matteo Giomi (Statice GmbH), Franziska Boenisch (Vector Institute), Christoph Wehmeyer (Statice GmbH), and Borbála Tasnádi (Statice GmbH) - Unintended Memorization and Timing Attacks in Named Entity Recognition Models
Rana Salal Ali (Macquarie University), Benjamin Zi Hao Zhao (Macquarie University), Hassan Asghar (Macquarie University), Tham Nguyen (Macquarie University), Ian Wood (Macquarie University), and Mohamed Ali Kaafar (Macquarie University) - RPM: Robust Anonymity at Scale
Donghang Lu (Purdue University) and Aniket Kate (Purdue University) - Private Sampling with Covert Cheaters
César Sabater (INRIA), Florian Hahn (University of Twente), Andreas Peter (University of Oldenburg), and Jan Ramon (INRIA) - Investigating how users imagine their Personal Privacy Assistant
Alina Stöver (TU Darmstadt), Sara Hahn (TU Darmstadt), Felix Kretschmer (), and Nina Gerber (TU Darmstadt) - SoK: Content Moderation for End-to-End Encryption
Sarah Scheffler (Princeton University) and Jonathan Mayer (Princeton University) - ezDPS: An Efficient and Zero-Knowledge Machine Learning Inference Pipeline
Haodi Wang (Beijing Normal University / Virginia Tech) and Thang Hoang (Virginia Tech) - Two-Cloud Private Read Alignment to a Public Reference Genome
Sindhuja Madabushi (University of Wisconsin-Madison) and Parameswaran Ramanathan (University of Wisconsin-Madison) - PubSub-ML: A Model Streaming Alternative to Federated Learning
Lovedeep Gondara (Simon Fraser University) and Ke Wang (Simon Fraser University) - SoK: Differentially Private Publication of Trajectory Data
Àlex Miranda-Pascual (Universitat Politècnica de Catalunya, Karlsruhe Institute of Technology), Patricia Guerra-Balboa (Karlsruhe Institute of Technology), Javier Parra-Arnau (Universitat Politècnica de Catalunya, Karlsruhe Institute of Technology), Jordi Forné (Universitat Politècnica de Catalunya), and Thorsten Strufe (Karlsruhe Institute of Technology) - An Efficient Data-Independent Priority Queue and its Application to Dark Pools
Sahar Mazloom (J. P. Morgan AI Research), Antigoni Polychroniadou (J. P. Morgan AI Research), Tucker Balch (J. P. Morgan AI Research), and Benjamin Diamond (J. P. Morgan AI Research) - Find Thy Neighbourhood: Privacy-Preserving Local Clustering
Pranav Shriram A (National Institute of Technology Tiruchirappalli), Nishat Koti (Indian Institute of Science Bangalore), Varsha Bhat Kukkala (Indian Institute of Science Bangalore), Arpita Patra (Indian Institute of Science Bangalore), and Bhavish Raj Gopal (Indian Institute of Science Bangalore) - Result-pattern-hiding Conjunctive Searchable Symmetric Encryption with Forward Privacy
Dandan Yuan (The University of Auckland), Cong Zuo (Nanyang Technological University), Shujie Cui (Monash University), and Giovanni Russello (The University of Auckland) - Private Graph Extraction via Feature Explanations
Iyiola Emmanuel Olatunji (L3S Research Center, Leibniz University Hannover), Mandeep Rathee (L3S Research Center, Leibniz University Hannover), Thorben Funke (L3S Research Center, Leibniz University Hannover), and Megha Khosla (TU Delft) - iStelan: Disclosing Sensitive User Information by Mobile Magnetometer from Finger Touches
Reham Aburas (Purdue University), Habiba Farrukh (Purdue University), He Wang (Purdue University), Yidong Lu (Purdue University), and Z. Berkay Celik (Purdue University) - SoK: Managing risks of linkage attacks on data privacy
Jovan Powar (University of Cambridge) and Alastair Beresford (University of Cambridge)
