Accepted papers for PETS 2025

Issue 1

  • Understanding Privacy Norms through Web Forms Artifact: Reproduced
    Hao Cui (University of California, Irvine), Rahmadi Trimananda (University of California, Irvine), and Athina Markopoulou (University of California, Irvine)
  • BehaVR: User Identification Based on VR Sensor Data Artifact: Available
    Ismat Jarin (University of California, Irvine), Yu Duan (University of California, Irvine), Rahmadi Trimananda (University of California, Irvine), Hao Cui (University of California, Irvine), Salma Elmalaki (University of California, Irvine), and Athina Markopoulou (University of California, Irvine)
  • Topology-Based Reconstruction Prevention for Decentralised Learning Artifact: Reproduced
    Florine W. Dekker (Delft University of Technology), Zekeriya Erkin (Delft University of Technology), and Mauro Conti (Università di Padova)
  • How Unique is Whose Web Browser? The role of demographics in browser fingerprinting among US users Artifact: Available
    Alex Berke (MIT Media Lab), Badih Ghazi (Google), Enrico Bacis (Google), Pritish Kamath (Google), Ravi Kumar (Google), Robin Lassonde (Google), Pasin Manurangsi (Google), and Umar Syed (Google)
  • Lightweight Two-Party Secure Sampling Protocol for Differential Privacy
    Masanobu Kii (NTT Social Information Laboratories), Atsunori Ichikawa (NTT Social Information Laboratories), and Takayuki Miura (NTT Social Information Laboratories)
  • SoK: Descriptive Statistics Under Local Differential Privacy Artifact: Reproduced
    René Raab (Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg), Pascal Berrang (University of Birmingham), Paul Gerhart (TU Wien), and Dominique Schröder (TU Wien)
  • User Privacy Perceptions Across the XR Spectrum: An Extended Reality Cross-Platform Comparative Analysis of A Virtual House Tour
    Chris Warin (University of Göttingen), Viktoriya Pak (University of Göttingen), and Delphine Reinhardt (University of Göttingen)
  • Privacy-preserving Multiple Sequence Alignment Scheme for Long Gene Sequence
    Yatong Jiang (Beihang University), Tao Shang (Beihang University), and Jianwe Liu (Beihang University)
  • Examining Caregiving Roles to Differentiate the Effects of Using a Mobile App for Community Oversight for Privacy and Security
    Mamtaj Akter (Vanderbilt University), Jess Kropczynski (University of Cincinnati), Heather Lipford (University of North Carolina, Charlotte), and Pamela Wisniewski (Vanderbilt University)
  • Mastic: Private Weighted Heavy-Hitters and Attribute-Based Metrics Artifact: Reproduced
    Dimitris Mouris (Nillion & University of Delaware), Christopher Patton (Cloudflare), Hannah Davis (Seagate), Pratik Sarkar (Supra Research), and Nektarios Georgios Tsoutsos (University of Delaware)
  • Real-world Deniability in Messaging Artifact: Reproduced
    Daniel Collins (EPFL and Purdue University), Simone Colombo (EPFL), and Loïs Huguenin-Dumittan (EPFL)
  • Practical Two-party Computational Differential Privacy with Active Security
    Fredrik Meisingseth (TU Graz), Fabian Schmid (TU Graz), and Christian Rechberger (TU Graz)
  • EpiOracle: Privacy-Preserving Cross-Facility EarlyWarning for Unknown Epidemics Artifact: Reproduced
    Shiyu Li (University of Electronic Science and Technology of China), Yuan Zhang (University of Electronic Science and Technology of China), Yaqing Song (University of Electronic Science and Technology of China), Fan Wu (Central South University), Feng Lyu (Central South University), Kan Yang (The University of Memphis), and Qiang Tang (The University of Sydney)
  • User-Centric Textual Descriptions of Privacy-Enhancing Technologies for Ad Tracking and Analytics
    Lu Xian (University of Michigan), Song Mi Lee-Kan (University of Michigan), Jane Im (University of Michigan), and Florian Schaub (University of Michigan)
  • WatchWitch: Interoperability, Privacy, and Autonomy for the Apple Watch
    Nils Rollshausen (TU Darmstadt), Alexander Heinrich (TU Darmstadt), Matthias Hollick (TU Darmstadt), and Jiska Classen (Hasso Plattner Institute)
  • SoK: Computational and Distributed Differential Privacy for MPC
    Fredrik Meisingseth (TU Graz) and Christian Rechberger (TU Graz)
  • Searchable Encryption for Conjunctive Queries with Extended Forward and Backward Privacy Artifact: Reproduced
    Cong Zuo (Beijing Institute of Technology), Shangqi Lai (Monash University/CSIRO Data61), Shi-Feng Sun (Shanghai Jiao Tong University), Xingliang Yuan (The University of Melbourne), Joseph K. Liu (Monash University), Jun Shao (Zhejiang Gongshang University/Zhejiang E-Commerce Key Lab), Huaxiong Wang (Nanyang Technological University), Liehuang Zhu (Beijing Institute of Technology), and Shujie Cui (Monash University)
  • Misalignments and Demographic Differences in Expected and Actual Privacy Settings on Facebook
    Byron Lowens (University of Michigan), Sean Scarnecchia (University of Michigan), Jane Im (University of Michigan), Tanisha Afnan (tafnan@umich.edu), Annie Chen (anniechn@umich.edu), Yixin Zou (Max Planck Institute for Security and Privacy), and Florian Schaub (University of Michigan)
  • SoK: (Un)usable Privacy: the Lack of Overlap between Privacy-Aware Sensing and Usable Privacy Research Artifact: Reproduced
    Yasha Iravantchi (University of Michigan), Pardis Emami-Naeini (Duke University), and Alanson Sample (University of Michigan)
  • Gig Work at What Cost?: Exploring Privacy Risks of Gig Work Platform Participation in the U.S.
    Amogh Pradeep (Northeastern University), Johanna Gunawan (Northeastern University), Alvaro Feal (Northeastern University), Woodrow Hartzog (Boston University), and David Choffnes (Northeastern University)
  • Janus: Fast Privacy-Preserving Data Provenance For TLS Artifact: Reproduced
    Jan Lauinger (Technical University of Munich), Jen Ernstberger (Technical University of Munich), Andreas Finkenzeller (Technical University of Munich), and Sebastian Steinhorst (Technical University of Munich)
  • Improving the Performance and Security of Tor’s Onion Services
    Arushi Arora (Purdue University) and Christina Garman (Purdue University)
  • Private Computation on Common Fuzzy Records
    Kyoohyung Han (Samsung SDS), Seongkwang Kim (Samsung SDS), and Yongha Son (Sungshin Women's University)
  • Communication-Efficient Differentially Private Federated Learning Using Second-Order Information
    Mounssif Krouka (University of Oulu), Antti Koskela (Nokia Bell Labs), and Tejas Kulkarni (Nokia Bell Labs)
  • A Comprehensive Study of Privacy Risks in Curriculum Learning
    Joann Qiongna Chen (University of California, Irvine), Xinlei He (The CISPA Helmholtz Center for Information Security), Zheng Li (The CISPA Helmholtz Center for Information Security), Yang Zhang (The CISPA Helmholtz Center for Information Security), and Zhou Li (University of California, Irvine)
  • PrePaMS: Privacy-Preserving Participant Management System for Studies with Rewards and Prerequisites Artifact: Reproduced
    Echo Meißner (Ulm University), Frank Kargl (Ulm University), Benjamin Erb (Ulm University), and Felix Engelmann (Lund University)
  • “It’s Not My Data Anymore”: Exploring Non-Users’ Privacy Perceptions of Medical Data Donation Apps
    Sarah Abdelwahab Gaballah (Ruhr University Bochum), Lamya Abdullah (Technical University of Darmstadt), Ephraim Zimmer (Technical University of Darmstadt), Sascha Fahl (CISPA Helmholtz Center for Information Security), Max Mühlhäuser (Technical University of Darmstadt), and Karola Marky (Ruhr University Bochum)
  • MixBuy: Contingent Payment in the Presence of Coin Mixers
    Diego Castejon-Molina (IMDEA Software Institute, Universidad Politécnica de Madrid), Dimitrios Vasilopoulos (IMDEA Software Institute), and Pedro Moreno-Sanchez (IMDEA Software Institute, VISA Research)
  • The Battery Insertion Attack: Is Periodic Pseudo-randomization Sufficient for Beacon Privacy?
    Liron David (Weizmann Institute of Science and Google Research), Moti Yung (Columbia University and Google Privacy, Security, and Safety Research), Avinatan Hassidim (Bar-Ilan University and Google Research), and Yossi Matias (Tel-Aviv University and Google Research)
  • Hardware-Accelerated Encrypted Execution of General-Purpose Applications
    Charles Gouert (University of Delaware), Vinu Joseph (NVIDIA), Steven Dalton (NVIDIA), Cedric Augonnet (NVIDIA), Michael Garland (NVIDIA), and Nektarios Georgios Tsoutsos (University of Delaware)
  • PrivacyGuard: Exploring Hidden Cross-App Privacy Leakage Threats In IoT Apps Artifact: Reproduced
    Zhaohui Wang (The University of Kansas), Bo Luo (The University of Kansas), and Fengjun Li (The University of Kansas)
  • Re-visiting Authorized Private Set Intersection: A New Privacy-Preserving Variant and Two Protocols Artifact: Available
    Francesca Falzon (ETH Zürich) and Evangelia Anna Markatou (TU Delft)
  • The Impact of Default Mobile SDK Usage on Privacy and Data Protection Artifact: Available
    Simon Koch (TU Braunschweig), Manuel Karl (TU Braunschweig), Robin Kirchner (TU Braunschweig), Malte Wessels (TU Braunschweig), Anne Paschke (TU Braunschweig), and Martin Johns (TU Braunschweig)
  • Noiseless Privacy-Preserving Decentralized Learning Artifact: Functional
    Sayan Biswas (EPFL), Mathieu Even (INRIA), Anne-Marie Kermarrec (EPFL), Laurent Massoulie (INRIA), Rafael Pires (EPFL), Rishi Sharma (EPFL), and Martijn de Vos (EPFL)
  • Towards Privacy-preserving and Fairness-aware Federated Learning Framework
    Adda Akram Bendoukha (Télécom SudParis, Institut Polytechnique de Paris), Didem Demirag (Université du Québec à Montréal (UQAM)), Nesrine Kaaniche (Samovar, Telecom-SudParis, Institut Polytechnique de Paris), Aymen Boudguiga (CEA List, Université Paris-Saclay), Renaud Sirdey (CEA List, Université Paris-Saclay), and Sébastien Gambs (Université du Québec à Montréal (UQAM))
  • RSA Blind Signatures with Public Metadata
    Ghous Amjad (Google), Kevin Yeo (Google and Columbia University), and Moti Yung (Google)
  • "What are they gonna do with my data?": Privacy Expectations, Concerns, and Behaviors in Virtual Reality
    Abhinaya S.B. (North Carolina State University), Abhishri Agrawal (UNC Chapel Hill), Yaxing Yao (Virginia Tech), Yixin Zou (Max Planck Institute for Security and Privacy), and Anupam Das (North Carolina State University)
  • Identifying Privacy Personas Artifact: Available
    Olena Hrynenko (Idiap Research Institute, École Polytechnique Fédérale de Lausanne) and Andrea Cavallaro (Idiap Research Institute, École Polytechnique Fédérale de Lausanne)
  • Beyond the Request: Harnessing HTTP Response Headers for Cross-Browser Web Tracker Classification in an Imbalanced Setting Artifact: Available
    Wolf Rieder (Technische Universität Berlin), Philip Raschke (Technische Universität Berlin), and Thomas Cory (Technische Universität Berlin)
  • Communication Efficient Secure and Private Multi-Party Deep Learning
    Sankha Das (Microsoft Research India), Sayak Ray Chowdhury (Microsoft Research India), Nishanth Chandran (Microsoft Research India), Divya Gupta (Microsoft Research India), Satya Lokam (Microsoft Research India), and Rahul Sharma (Microsoft Research India)
  • Revealing Hidden IoT Devices through Passive Detection, Fingerprinting, and Localization
    Wei Sun (UC San Diego), Hadi Givehchian (UC San Diego), and Dinesh Bharadia (UC San Diego)
  • DiDOTS: Knowledge Distillation from Large-Language-Models for Dementia Obfuscation in Transcribed Speech
    Dominika Woszczyk (Imperial College London) and Soteris Demetriou (Imperial College London)
  • Analyzing the Differentially Private Theil-Sen Estimator for Simple Linear Regression
    Jayshree Sarathy (Northeastern University) and Salil Vadhan (Harvard University)
  • High-Throughput Secure Multiparty Computation with an Honest Majority in Various Network Settings Artifact: Functional
    Christopher Harth-Kitzerow (Technical University of Munich (TUM), BMW Group), Ajith Suresh (Technology Innovation Institue (TII), Abu Dhabi), Yongqin Wang (University of Southern California (USC)), Hossein Yalame (Bosch GmbH, Germany), Georg Carle (Technical University of Munich (TUM)), and Murali Annavaram (University of Southern California (USC))
  • Practical, Private Assurance of the Value of Collaboration via Fully Homomorphic Encryption
    Hassan Asghar (Macquarie University), Zhigang Lu (Western Sydney University), Zhongrui Zhao (James Cook University), and Dali Kaafar (Macquarie University)
  • SpinML: Customized Synthetic Data Generation for Private Training of Specialized ML Models
    Jiang Zhang (University of Southern California), Rohan Sequeira (University of Southern California), and Konstantinos Psounis (University of Southern California)
  • ZIPNet: Low-bandwidth anonymous broadcast from (dis)Trusted Execution Environments
    Michael Rosenberg, Maurice Shih (University of Maryland), Zhenyu Zhao (Tsinghua University), Rui Wang (Purdue University), Ian Miers (University of Maryland), and Fan Zhang (Yale University)
  • The Impact of Generalization Techniques on the Interplay Among Privacy, Utility, and Fairness in Image Classification
    Ahmad Hassanpour (Norwegian University of Science and Technology), Amir Zarei (Norwegian University of Science and Technology), Khawla Mallat (SAP), Anderson Santana de Oliveira (SAP), and Bian Yang (Norwegian University of Science and Technology)
  • Privacy Perceptions and Behaviors Towards Targeted Advertising on Social Media: A Cross-Country Study
    Smirity Kaushik (University of Illinois Urbana Champaign), Tanusree Sharma (University of Illinois Urbana Champaign), Yaman Yu (University of Illinois Urbana Champaign), Amna F. Ali (University of Illinois Urbana Champaign), Bart Knijnenburg (Clemson University), Yang Wang (University of Illinois Urbana Champaign), and Yixin Zou (Max Planck Institute for Security and Privacy)
  • Privacy Settings of Third-Party Libraries in Android Apps: A Study of Facebook SDKs
    David Rodriguez (Universidad Politécnica de Madrid), Joseph A. Calandrino (), Jose M. Del Alamo (Universidad Politécnica de Madrid), and Norman Sadeh (Carnegie Mellon University)
  • Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study
    Ayana Moshruba (George Mason University), Ihsen Alouani (Queen's University Belfast), and Maryam Parsa (George Mason University)
  • Private Shared Random Minimum Spanning Forests
    Marian Dietz (ETH Zurich) and Florian Kerschbaum (University of Waterloo)

Issue 2

  • Understanding Regional Filter Lists: Efficacy and Impact
    Christian Böttger (Institute for Internet Security; Westphalian University of Applied Sciences), Nurullah Demir (Institute for Internet Security; Westphalian University of Applied Sciences), Jan Hörnemann (AWARE7 GmbH), Bhupendra Acharya (CISPA), Norbert Pohlmann (Institute for Internet Security; Westphalian University of Applied Sciences), Thorsten Holz (CISPA), Matteo Grosse-Kampmann (Rhine-Waal University of Applied Sciences and AWARE7 GmbH), and Tobias Urban (Institute for Internet Security; Westphalian University of Applied Sciences)
  • Time-Efficient Locally Relevant Geo-Location Privacy Protection
    Chenxi Qiu (University of North Texas), Ruiyao Liu (University of North Texas), Primal Pappachan (Portland State University), Anna Cinzia Squicciarini (Penn State University), and Xinpeng Xie (University of North Texas)
  • Automating Governing Knowledge Commons and Contextual Integrity (GKC-CI) Privacy Policy Annotations with Large Language Models
    Jake Chanenson (University of Chicago), Madison Pickering (University of Chicago), and Noah Apthorpe (Colgate University)
  • Can Social Media Privacy and Safety Features Protect Targets of Interpersonal Attacks? A Systematic Analysis
    Majed Almansoori (University of Wisconsin-Madison and United Arab Emirates University (UAEU)) and Rahul Chatterjee (University of Wisconsin-Madison)
  • VIMz: Private Proofs of Image Manipulation using Folding-based zkSNARKs
    Stefan Dziembowski (University of Warsaw / IDEAS NCBR), Shahriar Ebrahimi (IDEAS NCBR), and Parisa Hassanizadeh (IDEAS NCBR / IPPT PAN)
  • To Reveal or Conceal: Privacy and Marginalization in Avatars
    Mattea Sim (Indiana University), Basia Radka (University of Washington), Emi Yoshikawa (University of Washington), Franziska Roesner (University of Washington), Kurt Hugenberg (Indiana University), and Tadayoshi Kohno (University of Washington)
  • The Last Hop Attack: Why Loop Cover Traffic over Fixed Cascades Threatens Anonymity
    Maximilian Weisenseel (TU Dresden), Christoph Döpmann (TU Berlin), and Florian Tschorsch (TU Dresden)
  • White-box Membership Inference Attacks against Diffusion Models
    Yan Pang (University of Virginia), Tianhao Wang (University of Virginia), Xuhui Kang (University of Virginia), Mengdi Huai (Iowa State University), and Yang Zhang (CISPA Helmholtz Center for Information Security)
  • ORIGO: Proving Provenance of Sensitive Data with Constant Communication
    Jens Ernstberger (Technical University of Munich), Jan Lauinger (Technical University of Munich), Yinnan Wu (Technical University of Munich), Arthur Gervais (University College London), and Sebastian Steinhorst (Technical University of Munich)
  • DB-PAISA: Discovery-Based Privacy-Agile IoT Sensing+Actuation
    Isita Bagayatkar (University of California, Irvine), Youngil Kim (University of California, Irvine), and Gene Tsudik (University of California, Irvine)
  • PGUP: Pretty Good User Privacy for 5G-enabled Secure Mobile Communication Protocols
    Rabiah Alnashwan (University of Sheffield), Prosanta Gope (University of Sheffield), and Benjamin Dowling (University of Sheffield)
  • SecurED: Secure Multiparty Edit Distance for Genomic Sequences
    Jiahui Gao (Arizona State University), Yagaagowtham Palanikuma (Arizona State University), Dimitris Mouris (Nillion), Duong Nguyen (Arizona State University), and Ni Trieu (Arizona State University)
  • SoK: The Spectre of Surveillance and Censorship in Future Internet Architectures
    Michael Wrana (University of Waterloo), Diogo Barradas (University of Waterloo), and N Asokan (University of Waterloo)
  • Onion-Location Measurements and Fingerprinting
    Paul Syverson (U.S. Naval Research Laboratory), Rasmus Dahlberg (Independent), Tobias Pulls (Karlstad University), and Rob Jansen (U.S. Naval Research Laboratory)
  • Oryx: Private detection of cycles in federated graphs
    Ke Zhong (University of Pennsylvania) and Sebastian Angel (University of Pennsylvania)
  • Efficient Verifiable Differential Privacy with Input Authenticity in the Local and Shuffle Model
    Tariq Bontekoe (University of Groningen), Hassan Jameel Asghar (Macquarie University), and Fatih Turkmen (University of Groningen)
  • RPKI-based Location-Unaware Tor Guard Relay Selection Algorithms
    Zhifan Lu (University of Virginia), Siyang Sun (University of Virginia), and Yixin Sun (University of Virginia)
  • MProve-Nova: A Privacy-Preserving Proof of Reserves Protocol for Monero
    Varun Thakore (Indian Institute of Technology Bombay) and Saravanan Vijayakumaran (Indian Institute of Technology Bombay)
  • Recycling Scraps: Improving Private Learning by Leveraging Checkpoints
    Virat Vishnu Shejwalkar (Google Deepmind), Arun Ganesh (Google Research), Rajiv Mathews (Google), Yarong Mu (Google), Shuang Song (Google Deepmind), Om Thakkar (OpenAI), Abhradeep Thakurta (Google Deepmind), and Xinyi Zheng (Google)
  • OPPID: Single Sign-On with Oblivious Pairwise Pseudonyms
    Maximilian Kroschewski (Hasso Plattner Institute, University of Potsdam), Anja Lehmann (Hasso Plattner Institute, University of Potsdam), and Cavit Özbay (Hasso Plattner Institute, University of Potsdam)
  • Enhancing Metric Privacy With a Shuffler
    Andreas Athanasiou (INRIA, École polytechnique), Catuscia Palamidessi (Inria), and Kostas Chatzikokolakis (Inria, National and Kapodistrian University of Athens)
  • Maliciously Secure Circuit Private Set Intersection via SPDZ-Compatible Oblivious PRF
    Yaxi Yang (Singapore University of Technology and Design), Xiaojian Liang (Ant International, Ant Group, China), Xiangfu Song (National University of Singapore), Ye Dong (Singapore University of Technology and Design), Linting Huang (Guangzhou University), Hongyu Ren (Guangzhou University), Changyu Dong (Guangzhou University), and Jianying Zhou (Singapore University of Technology and Design)
  • Wave Hello to Privacy - Efficient Mixed-Mode MPC using Wavelet Transforms
    José Reis (NIllion), Mehmet Ugurbil (Nillion), Sameer Wagh (SecretBit Ventures LLC), Ryan Henry (University of Calgary), and Miguel de Vega (Nillion)
  • Why Am I Seeing Double? An Investigation of Device Management Flaws in Voice Assistant Platforms
    Muslum Ozgur Ozmen (Arizona State University), Mehmet Oguz Sakaoglu (Purdue University), Jackson Bizjak (Purdue University), Jianliang Wu (Simon Fraser University), Antonio Bianchi (Purdue University), Dave (Jing) Tian (Purdue University), and Z. Berkay Celik (Purdue University)
  • TETRIS: Composing FHE Techniques for Private Functional Exploration Over Large Datasets
    Malika IZABACHENE (Independent) and Jean-Philippe BOSSUAT (Independent)
  • Unlearning Clients, Features and Samples in Vertical Federated Learning
    Ayush Kumar Varshney (Umeå University), Konstantinos Vandikas (Ericsson), and Vicenç Torra (Umeå University)
  • DiffPrivate: Facial Privacy Protection with Diffusion Models
    Minh-Ha Le (Linköping University) and Niklas Carlsson (Linköping University)
  • The Effect of Platform Policies on App Privacy Compliance
    Noura Alomar (University of California (Berkeley)), Joel Reardon (University of Calgary), Aniketh Girish (IMDEA Networks Institute and Universidad Carlos III de Madrid), Narseo Vallina-Rodriguez (IMDEA Networks Institute), and Serge Egelman (University of California, Berkeley and International Computer Science Institute)
  • Echoes of Privacy: Uncovering the Profiling Practices of Voice Assistants
    Tina Khezresmaeilzadeh (University of Southern California), Elaine Zhu (Northeastern University), Kiersten Grieco (Northeastern University), Daniel J. Dubois (Northeastern University), Konstantinos Psounis (University of Southern California), and David Choffnes (Northeastern University)
  • AnoFel: Supporting Anonymity for Privacy-Preserving Federated Learning
    Ghada Almashaqbeh (University of Connecticut) and Zahra Ghodsi (Purdue University)
  • Surveillance Disguised as Protection: A Comparative Analysis of Sideloaded and In-Store Parental Control Apps
    Eva-Maria Maier (FH St. Pölten), Leonie Tanczer (University College London), and Lukas Daniel Klausner (FH St. Pölten)
  • Unmasking the Shadows: A Cross-Country Study of Online Tracking in Illegal Movie Streaming Services
    Hussein Sheaib (Saarland University), Anja Feldmann (Max-Planck-Institut für Informatik), and Ha Dao (Max-Planck-Institut für Informatik)
  • Empirically Measuring Data Localization in the EU
    Alexander Gamero-Garrido (UC Davis), Kicho Yu (USC), Sumukh Vasisht Shankar (Yale University), Sachin Kumar Singh (University of Utah), Sindhya Balasubramanian (Northeastern University), Alexander Wilcox (Northeastern University), and David Choffnes (Northeastern University)
  • "Free WiFi is not ultimately free": Privacy Perceptions of Users in the US regarding City-wide WiFi Services
    Prianka Mandal (William & Mary), Tu Le (UC Irvine), Amit Seal Ami (William & Mary), Yuan Tian (UCLA), and Adwait Nadkarni (William & Mary)
  • Evaluating a Data Fiduciary Standard for Privacy: Developer and End-user Perspectives
    Michele Tang (Pomona College), Liam Bayer Jr. (Pomona College), Leonardo Torres (Pomona College), and Eleanor Birrell (Pomona College)
  • Privacy and Security of FIDO2 Revisited
    Manuel Barbosa (Universidade do Porto (FCUP) & INESC TEC & Max Planck Institute for Security and Privacy), Alexandra Boldyreva (Georgia Institute of Technology), Shan Chen (Southern University of Science and Technology), Kaishuo Cheng (Georgia Institute of Technology), and Luis Esquivel (Universidade do Porto (FCUP) & INESC TEC)

Issue 3

  • "AI is from the devil." Behaviors and Concerns Toward Personal Data Sharing with LLM-based Conversational Agents
    Noé Zufferey (ETH Zurich), Sarah Abdelwahab Gaballah (Ruhr University Bochum), Karola Marky (Ruhr University Bochum), and Verena Zimmermann (ETH Zurich)
  • Locally Differentially Private Frequency Estimation via Joint Randomized Response
    Ye Zheng (Rochester Institute of Technology), Shafizur Rahman Seeam (Rochester Institute of Technology), Yidan Hu (Rochester Institute of Technology), Rui Zhang (University of Delaware), and Yanchao Zhang (Arizona State University)
  • Referrer Policy: Implementation and Circumvention
    Luqman Muhammad Zagi (Radboud University), Zahra Moti (Radboud University), and Gunes Acar (Radboud University)
  • Learning Privacy from Visual Entities
    Alessio Xompero (Queen Mary University of London) and Andrea Cavallaro (Idiap Research Institute)
  • Teaching an Old Dog New Tricks: Verifiable FHE Using Commodity Hardware
    Jules Drean (MIT), Fisher Jepsen (MIT), Edward Suh (NVIDIA), Srinivas Devadas (MIT), Aamer Jaleel (NVIDIA), and Gururaj Saileshwar (University of Toronto)
  • Vote&Check: Secure Postal Voting with Reduced Trust Assumptions
    Véronique Cortier (CNRS, Nancy), Alexandre Debant (Inria Nancy, France), Pierrick Gaudry (CNRS, Nancy), and Léo Louistisserand (CNRS, Nancy)
  • Does Coding Style Really Survive Compilation? Stylometry of Executable Code Revisited
    Muaz Ali (University of Arizona), Tugay Biglis (University of Arizona), Nimet Beyza Bozdag (University of Arizona), Saumya Debray (University of Arizona), and Sazzadur Rahaman (University of Arizona)
  • Your Signal, Their Data: An Empirical Privacy Analysis of Wireless-scanning SDKs in Android
    Aniketh Girish (IMDEA Networks Institute / Universidad Carlos III de Madrid), Joel Reardon (University of Calgary), Srdjan Matic (IMDEA Software Institute), Juan Tapiador (Universidad Carlos III de Madrid), and Narseo Vallina-Rodriguez (IMDEA Networks Institute)
  • On the Differential Privacy and Interactivity of Privacy Sandbox Reports
    Badih Ghazi (Google Research), Charlie Harrison (Google), Pritish Kamath (Google Research), Alexander Knop (Google Research), Ravi Kumar (Google Research), Ethan Leeman (Google), Pasin Manurangsi (Google Research), Vikas Sahu (Google), Arpana Hosabettu (Google), Mariana Raykova (Google Research), and Phillipp Schoppmann (Google Research)
  • Panopticon: The Design and Evaluation of a Game that Teaches Data Science Students Designing Privacy
    Yuhe Tian (University of California, San Diego), Shao-Yu Chu (University of California, San Diego), Yuxuan Liu (University of California, San Diego), and Haojian Jin (University of California, San Diego)
  • SCIF: Privacy-Preserving Statistics Collection with Input Validation and Full Security
    Jianan Su (Georgetown University), Laasya Bangalore (SandboxAQ), Harel Berger (Georgetown University), Jason Yi (Georgetown University), Sophia Castor (Georgetown University), Muthuramakrishnan Venkitasubramaniam (Georgetown University), and Micah Sherr (Georgetown University)
  • Low-Cost Privacy-Preserving Decentralized Learning
    Sayan Biswas (EPFL), Davide Frey (University of Rennes, Inria Rennes, IRISA), Romaric Gaudel (University of Rennes, Inria Rennes, IRISA), Anne-Marie Kermarrec (EPFL), Dimitri Lerévérend (University of Rennes, Inria Rennes, IRISA), Rafael Pires (EPFL), Rishi Sharma (EPFL), and François Taïani (University of Rennes, Inria Rennes, IRISA)
  • Unbalanced Private Set Intersection from Client-Independent Relaxed Oblivious PRF
    Xiaodong Wang (Tsinghua University), Zijie Lu (Beijing Institute of Mathematical Sciences and Applications), Bei Liang (Beijing Institute of Mathematical Sciences and Applications), and Shengzhe Meng (Tsinghua University)
  • WaKA: Data Attribution with Privacy Principles]{WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles
    Patrick Mesana (HEC Montreal), Sébastien Gambs (University du Québec à Montréal), Clément Bénesse (University du Québec à Montréal), Hadrien Lautraite (University du Québec à Montréal), and Gilles Caporossi (HEC Montréal)
  • Stochastic Models for Remote Timing Attacks
    Simone Bozzolan (Università Ca' Foscari Venezia), Diletta Olliaro (Università Ca' Foscari Venezia), Stefano Calzavara (Università Ca' Foscari Venezia), Andrea Marin (Università Ca' Foscari Venezia), Gianfranco Balbo (Università di Torino), and Matteo Sereno (Università di Torino)
  • SoK: Web Authentication and Recovery in the Age of End-to-End Encryption
    Jenny Blessing (University of Cambridge), Daniel Hugenroth (University of Cambridge), Ross J. Anderson (University of Cambridge & Edinburgh), and Alastair R. Beresford (University of Cambridge)
  • Differentially Private Release of Hierarchical Origin/Destination Data with a TopDown Approach
    Fabrizio Boninsegna (University of Padova) and Francesco Silvestri (University of Padova)
  • Achieving Data Reconstruction Hardness and Efficient Computation in Multiparty Minimax Training
    Truong Son Nguyen (Arizona State University), Yi Ren (Arizona State University), Guangyu Nie (Arizona State University), and Ni Trieu (Arizona State University)
  • GNNBleed: Inference Attacks to Unveil Private Edges in Graphs with Realistic Access to GNN Models
    Zeyu Song (The Pennsylvania State University), Ehsanul Kabir (The Pennsylvania State University), and Shagufta Mehnaz (Penn State University)
  • PIGEON: A High Throughput Framework for Private Inference of Neural Networks using Secure Multiparty Computation
    Christopher Harth-Kitzerow (Technical University of Munich, BMW Group), Yongqin Wang (University of Southern California), Rachit Rajat (University of Southern California), Georg Carle (Technical University of Munich), and Murali Annavaram (University of Southern California)
  • Who Cares? Contextual Privacy Norms from Owner and Bystander Perspectives in Different Smart Home Situations
    Alisa Frik (International Computer Science Institute), Xiao Zhan (King's College London), Noura Abdi (Liverpool Hope University), and Julia Bernd (International Computer Science Institute)
  • A non-comparison oblivious sort and its application to private k-NN
    Sofiane Azogagh (University of Quebec at Montreal), Marc-Olivier Killijian (University of Quebec at Montreal), and Félix Larose-Gervais (University of Quebec at Montreal)
  • Client-Efficient Online-Offline Private Information Retrieval
    Hoang-Dung Nguyen (Virginia Tech), Jorge Guajardo (Robert Bosch LLC - Research and Technology Center), and Thang Hoang (Virginia Tech)
  • Tracker Installations Are Not Created Equal: Understanding Tracker Configuration of Form Data Collection
    Julia Kieserman (New York University), Athanasios Andreou (New York University), Chris Geeng (Northeastern University), Tobias Lauinger (New York University), and Damon McCoy (New York University)
  • Understanding User Privacy Perceptions in Video Conferencing: Insights from a Feature-Specific User Study
    Hobin Kim (KAIST), Wonho Song (KAIST), Joseph Seering (KAIST), and Min Suk Kang (KAIST)
  • Meta-Learn to Unlearn: Enhanced Exact Machine Unlearning in Recommendation Systems with Meta-Learning
    Abdulla Alshabanah (University of Southern California), Keshav Balasubramanian (University of Southern California), and Murali Annavaram (University of Southern California)
  • My Data or Our Data? Exploring Adult Users' Experiences with Apple's Family Sharing
    Amel Bourdoucen (Aalto University) and Janne Lindqvist (Aalto University)
  • Making Web Applications GDPR Compliant: A Comparative Evaluation of GDPR-Enforcement Frameworks
    Felix Kalinowski (Ruhr University Bochum), David Klein (Technische Universität Braunschweig), Martin Johns (Technische Universität Braunschweig), and Veelasha Moonsamy (Ruhr University Bochum)
  • Rethinking Fingerprinting: An Assessment of Behavior-based Methods at Scale and Implications for Web Tracking
    Kyle Crichton (Georgetown University), Lorrie Faith Cranor (Carnegie Mellon University), and Nicolas Christin (Carnegie Mellon University)
  • "Hoovered Up as a Data Point'': Exploring Privacy Behaviours, Awareness, and Concerns Among UK Users of LLM-based Conversational Agents
    Lisa Malki (University College London), Akhil Polamarasetty (University College London), Majid Hatamian (Google), Enrico Costanza (University College London), and Mark Warner (University College London)
  • TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks
    Mohammadmahdi Maheri (Imperial College London), Hamed Haddadi (Imperial College London & Brave Software), and Alex Davidson (NOVA LINCS, Universidade NOVA de Lisboa)
  • SoK: Usability Studies in Differential Privacy
    Onyinye Dibia (University of Vermont), Prianka Bhattacharjee (University of Vermont), Brad Stenger (University of Vermont), Steven Baldasty (University of Vermont), Mako Bates (University of Vermont), Ivoline Ngong (University of Vermont), Yuanyuan Feng (University of Vermont), and Joseph P. Near (University of Vermont)
  • Blocking Resistant Communication for Censorship Circumvention using Push Notification
    Piyush Kumar (University of Michigan), Diwen Xue (University of Michigan), Aaron Ortwein (University of Michigan), Cecylia Bocovich (The Tor Project), Harry (Independent), and Roya Ensafi (University of Michigan)
  • Hypersphere Secure Sketch Revisited: Probabilistic Linear Regression Attack on IronMask in Multiple Usage
    Pengxu Zhu (Shanghai Jiao Tong University) and Lei Wang (Shanghai Jiao Tong University)
  • A (web)View to a Kill: An Empirical Analysis of Privacy Threats in Hybrid Mobile Android Apps
    Nipuna Weerasekara (IMDEA Networks Institute), José Miguel Moreno (Universidad Carlos III de Madrid), Srdjan Matic (IMDEA Software Institute), Joel Reardon (University of Calgary), Juan Tapiador (Universidad Carlos III de Madrid), and Narseo Vallina-Rodriguez (IMDEA Networks Institute)
  • Uncovering the APP Cloud Access Risks under Recommended IAM Security Practices
    Hengtong Lu (Institute of Information Engineering, CAS, China), Yan Zhang (Institute of Information Engineering, CAS, China), Pengwei Zhan (Institute of Information Engineering, CAS, China), and Qingfeng Tang (Macau University of Science and Technology)

Issue 4

  • Models Matter: Setting Accurate Privacy Expectations for Local and Central Differential Privacy
    Mary Anne Smart (Purdue University), Priyanka Nanayakkara (Harvard University), Rachel Cummings (Columbia University), Gabriel Kaptchuk (University of Maryland, College Park), and Elissa Redmiles (Georgetown University)
  • Message Authentication Code with Fast Verification over Encrypted Data and Applications
    Adi Akavia (University of Haifa), Meir Goldenberg (University of Haifa), Neta Oren (University of Haifa), and Margarita Vald (Intuit Israel Ltd.)
  • Optimal Piecewise-based Mechanism for Collecting Bounded Numerical Data under Local Differential Privacy
    Ye Zheng (Rochester Institute of Technology), Sumita Mishra (Rochester Institute of Technology), and Yidan Hu (Rochester Institute of Technology)
  • Locally Differentially Private Group Comparison in Decentralized Health Data
    René Raab (Friedrich-Alexander-Universität Erlangen-Nürnberg), Arijana Bohr (Friedrich-Alexander-Universität Erlangen-Nürnberg), Kai Klede (Friedrich-Alexander-Universität Erlangen-Nürnberg), Benjamin Gmeiner (Novartis Pharma GmbH), and Bjoern M. Eskofier (Friedrich-Alexander-Universität Erlangen-Nürnberg)
  • HyDia: FHE-based Facial Matching with Hybrid Approximations and Diagonalization
    Sam Martin (University of Notre Dame), Nirajan Koirala (University of Notre Dame), Helena Berens (University of Notre Dame), Tommy Rozgonyi (University of Notre Dame), Micah Brody (University of Notre Dame), and Taeho Jung (University of Notre Dame)
  • Sybil-Resistant Parallel Mixnets
    Maya Kleinstein (Hebrew University of Jerusalem), Riad S. Wahby (Carnegie Mellon University), and Yossi Gilad (Hebrew University of Jerusalem)
  • What WeChat Knows: Pervasive First-Party Tracking in a Billion-User Super-App Ecosystem
    Mona Wang (Princeton University), Pellaeon Lin (Citizen Lab, University of Toronto), Jeffrey Knockel (Citizen Lab, University of Toronto), Will Greenberg (Electronic Frontier Foundation), Jonathan Mayer (Princeton University), and Prateek Mittal (Princeton University)
  • Buy it Now, Track Me Later: Attacking User Privacy via Wi-Fi AP Online Auctions
    Steven Su (University of Maryland), Erik Rye (University of Maryland), Dave Levin (University of Maryland), and Robert Beverly (San Diego State University)
  • Toxic Decoys: A Path to Scaling Privacy-Preserving Cryptocurrencies
    Christian Cachin (University of Bern, Institute of Computer Science) and François-Xavier Wicht (University of Bern, Institute of Computer Science)
  • MultiCent: Secure and Scalable Centrality Measures on Multilayer Graphs
    Andreas Brüggemann (TU Darmstadt), Nishat Koti (Aztec Labs), Varsha Bhat Kukkala (IIT Tirupati), and Thomas Schneider (TU Darmstadt)
  • "Do It to Know It": Reshaping the Privacy Mindset of Computer Science Undergraduates
    Maisha Boteju (University of Auckland), Danielle Lottridge (University of Auckland), Thilina Ranbaduge (Data61, CSIRO), Dinusha Vatsalan (Macquarie University), and Ni Ding (University of Auckland)
  • Silent Splitter: Privacy for Payment Splitting via New Protocols for Distributed Point Functions
    Margaret Pierce (University of North Carolina at Chapel Hill) and Saba Eskandarian (University of North Carolina at Chapel Hill)
  • Understanding the Perils of YouTube's Privacy Settings on Ad Safety
    Cat Mai (New York University), Lexie Barthelemess (New York University), Bruno Coelho (New York University), Julia Kieserman (New York University), Kyle Spinelli (New York University), Eric Yang (State University of New York at Buffalo), Athanasios Andreou (New York University), Rachel Greenstadt (New York University), Tobias Lauinger (New York University), and Damon McCoy (New York University)
  • "If You Want to Encrypt It Really, Really Hardcore...": User Perceptions of Key Transparency in WhatsApp
    Konstantin Fischer (Ruhr University Bochum), Markus Keil (Ruhr University Bochum), Annalina Buckmann (Ruhr University Bochum), and M. Angela Sasse (Ruhr University Bochum)
  • Non-Interactive Verifiable Aggregation
    Ojaswi Acharya (University of Massachusetts Amherst), Suvasree Biswas (George Washington University), Weiqi Feng (University of Massachusetts Amherst), Adam O'Neill (University of Massachusetts Amherst), and Arkady Yerukhimovich (George Washington University)
  • Optimizing Encrypted Neural Networks: Model Design, Quantization and Fine-Tuning Using FHEW/TFHE
    Yu-Te Ku (Data Science Degree Program, National Taiwan University and Academia Sinica), Feng-Hao Liu (Washington State University), Chih-Fan Hsu (Inventec Corporation), Ming-Ching Chang (State University of New York, University at Albany), Shih-Hao Hung (High Performance and Scientific Computing Center, National Taiwan University), I-Ping Tu (Institute of Statistical Science, Academia Sinica), and Wei-Chao Chen (Inventec Corporation)
  • LANGuard: Analysing and Protecting Local Network Access on Mobile Devices
    Angelos Beitis (DistriNet,KU Leuven), Jeroen Robben (DistriNet,KU Leuven), Alexander Heinrich (SEEMOO, TU Darmstadt), Zhen Lei (Taiyuan University of Technology), Yijia Li (Taiyuan University of Technology), Nian Xue (Shandong University of Technology), Yongle Chen (Taiyuan University of Technology), Vik Vanderlinden (DistriNet, KU Leuven), and Mathy Vanhoef (DistriNet, KU Leuven)
  • Lost in Translation: Exploring the Risks of Web-to-Cross-platform Application Migration
    Claudio Paloscia (University of Illinois Chicago), Kostas Solomos (University of Illinois Chicago), Mir Masood Ali (University of Illinois Chicago), and Jason Polakis (University of Illinois Chicago)
  • PrivDiffuser: Privacy-Guided Diffusion Model for Data Obfuscation in Sensor Networks
    Xin Yang (University of Alberta) and Omid Ardakanian (University of Alberta)
  • TEEMS: A Trusted Execution Environment based Metadata-protected Messaging System
    Sajin Sasy (CISPA Helmholtz Center for Information Security), Aaron Johnson (U.S. Naval Research Laboratory), and Ian Goldberg (University of Waterloo)
  • "Erasing the Echo'': The Usability of Data Deletion in Smart Personal Assistants
    Cheng Cheng (University of Bristol) and Kopo Marvin Ramokapane (University of Bristol)
  • An Analysis of Censorship Bias in LLMs
    Mohamed Ahmed (Citizen Lab, University of Toronto), Jeffrey Knockel (Citizen Lab, University of Toronto), and Rachel Greenstadt (New York University)
  • Improved Open-World Fingerprinting Increases Threat to Streaming Video Privacy but Realistic Scenarios Remain Difficult
    Timothy Walsh (Naval Postgraduate School), Armon Barton (Naval Postgraduate School), and Mathias Kolsch (Naval Postgraduate School)
  • Measuring the Accuracy and Effectiveness of PII Removal Services
    Jiahui HE (The Hong Kong University of Science and Technology (Guangzhou)), Pete Snyder (Brave Software Inc), Hamed Haddadi (Imperial College London and Brave Software Inc), Fabi'an E. Bustamante (Northwestern University), and Gareth Tyson (The Hong Kong University of Science and Technology (Guangzhou))
  • Robust and Efficient Watermarking of Large Language Models Using Error Correction Codes
    Xiaokun Luan (Peking University), Zeming Wei (Peking University), Yihao Zhang (Peking University), and Meng Sun (Peking University)
  • Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation
    Haonan Shi (Case Western Reserve University), Tu Ouyang (Case Western Reserve University), and An Wang (Case Western Reserve University)
  • Help Me Help You: Privacy Considerations for Third Party IoT Device Repair
    Weijia He (University of Southampton), Nathan Reitinger (University of Maryland), Denise Anthony (University of Michigan), Chelsea Bruno (University of Michigan), Susan Landau (Tufts University), Carl A. Gunter (University of Illinois at Urbana-Champaign), Mounib Khanafer (American University of Kuwait), and Ravindra Mangar (Dartmouth College)
  • Leaky Diffusion: Attribute Leakage in Text-Guided Image Generation
    Anastasios Lepipas (Imperial College London), Marios Charalambides (Imperial College London), Jiani Liu (Imperial College London), Yiying Guan (Imperial College London), Dominika C Woszczyk (Imperial College London), Mansi (Imperial College London), Thanh Hai Le (Imperial College London), and Soteris Demetriou (Imperial College London)
  • Aimless Onions: Mixing without Topology Information
    Daniel Schadt (Karlsruhe Institute of Technology), Christoph Coijanovic (Karlsruhe Institute of Technology), and Thorsten Strufe (Karlsruhe Institute of Technology)
  • Match Quest: Fast and Secure Pattern Matching
    Pranav Jangir (New York University), Nishat Koti (Aztec Labs), Varsha Bhat Kukkala (IIT Tirupati), Arpita Patra (Indian Institute of Science), and Bhavish Raj Gopal (Indian Institute of Science)
  • Johnny Can't Revoke Consent Either: Measuring Compliance of Consent Revocation on the Web
    Gayatri Priyadarsini Kancherla (Indian Institute of Technology, Gandhinagar), Nataliia Bielova (Inria Centre at Université Côte d’Azur), Cristiana Santos (Utrecht University, Netherlands), and Abhishek Bichhawat (Indian Institute of Technology, Gandhinagar)
  • AlphaFL: Secure Aggregation with Malicious2 Security for Federated Learning against Dishonest Majority
    Yufan Jiang (Karlsruhe Institute of Technology), Maryam Zarezadeh (Barkhausen Institut), Tianxiang Dai (Lancaster University Leipzig), and Stefan Köpsell (Barkhausen Institut)
  • Truncation Untangled: Scaling Fixed-Point Arithmetic for Privacy-Preserving Machine Learning to Large Models and Datasets
    Christopher Harth-Kitzerow (Technical University of Munich, BMW Group), Ajith Suresh (Technology Innovation Institute (TII), Abu Dhabi), and Georg Carle (Technical University of Munich)
  • Privacy Bills of Materials (PriBOM): A Transparent Privacy Information Inventory for Collaborative Privacy Notice Generation in Mobile App Development
    Zhen Tao (Australian National University & CSIRO's Data61), Shidong Pan (Columbia University & New York University), Zhenchang Xing (CSIRO's Data61), Xiaoyu Sun (Australian National University), Omar Haggag (Monash University), John Grundy (Monash University), Jingjie Li (University of Edinburgh), and Liming Zhu (CSIRO's Data61 & School of CSE, UNSW)
  • Mission: Impossible - Image Based Geolocation with Large Vision Language Models
    Yi Liu (Quantstamp), Gelei Deng (Nanyang Technological University), Junchen Ding (University of New South Wales), Yuekang Li (University of New South Wales), Tianwei Zhang (Nanyang Technological University), Weisong Sun (Nanyang Technological University), Yaowen Zheng (Institute of Information Engineering, Chinese Acadamy of Sciences), and Jingquan Ge (Nanyang Technological University)
  • Intractable Cookie Crumbs: Unveiling the Nexus of Stateful Banner Interaction and Tracking Cookies
    Ali Rasaii (Max Planck Institute for Informatics), Ha Dao (Max Planck Institute for Informatics), Anja Feldmann (Max Planck Institute for Informatics), Mohammadmahdi Javid (Saarland University), Oliver Gasser (IPinfo), and Devashish Gosain (Indian Institute of Technology Bombay)
  • Akeso: Bringing Post-Compromise Security to Cloud Storage
    Lily Gloudemans (William & Mary), Pankaj Niroula (William & Mary), Aashutosh Poudel (William & Mary), and Stephen Herwig (William & Mary)
  • Path to Encrypted DNS with DDR: Adoption, Configuration Patterns, and Privacy Implications
    Vasilis Ververis (Hasso-Plattner-Institute / University of Potsdam), Steffen Sassalla (Hasso-Plattner-Institute / University of Potsdam), and Vaibhav Bajpai (Hasso-Plattner-Institute / University of Potsdam)
  • Private Knowledge Sharing in Distributed Learning
    Jumera Yasas Supeksala Akurudda Liyanage Don (Swinburne University of Technology (Hawthorn, VIC)), Thilina Ranbaduge (DATA61-CSIRO), Ming Ding (DATA61-CSIRO), Dinh C. Nguyen (University of Alabama in Huntsville), Bo Liu (University of Technology Sydney), Calson Chua (Swinburne University of Technology), and Jun Zhang (Swinburne University of Technology)
  • Sheep's clothing, wolfish impact: Automated detection and evaluation of problematic 'allowed' advertisements
    Ritik Roongta (New York University), Julia Jose (New York University), Hussam Habib (New York University), and Rachel Greenstadt (New York University)
  • Who’s Watching You Zoom? Investigating Privacy of Third-Party Zoom Apps
    Saharsh Goenka (Arizona State University), Adit Prabhu (Arizona State University), Payge Sakurai (Arizona State University), Mrinaal Ramachandran (Arizona State University), and Rakibul Hasan (Arizona State University)
  • Defining Privacy Engineering as a Profession
    Nikita Samarin (University of California, Berkeley), Nandita Rao Narla (Future of Privacy Forum), Liam Webster (University of California, Berkeley), and Daniel Smullen (CableLabs)
  • TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
    Marco Di Gennaro (Politecnico di Milano), Giovanni De Lucia (Politecnico di Milano), Stefano Longari (Politecnico di Milano), Stefano Zanero (Politecnico di Milano), and Michele Carminati (Politecnico di Milano)
  • Okay Google, Where’s My Tracker? Security, Privacy, and Performance Evaluation of Google’s Find My Device Network
    Leon Böttger (SEEMOO, TU Darmstadt), Alexander Heinrich (SEEMOO, TU Darmstadt), Dennis Arndt (SEEMOO, TU Darmstadt), and Matthias Hollick (SEEMOO, TU Darmstadt)
  • Navigating Social Media Privacy: Awareness, Preferences, and Discoverability
    Pithayuth Charnsethikul (University of Southern California Information Sciences Institute), Almajd Zunquti (University of Southern California Information Sciences Institute), Gale Lucas (University of Southern California Institute for Creative Technologies), and Jelena Mirkovic (University of Southern California Information Sciences Institute)