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Towards a common performance and effectiveness terminology for digital proximity tracing applications
Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a ...
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Synthetic Data – A Privacy Mirage
Synthetic datasets drawn from generative models have been advertised as ...
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The Bayes Security Measure
Security system designers favor worst-case security measures, such as th...
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Privacy Engineering Meets Software Engineering. On the Challenges of Engineering Privacy ByDesign
Current day software development relies heavily on the use of service ar...
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Datashare: A Decentralized Privacy-Preserving Search Engine for Investigative Journalists
Investigative journalists collect large numbers of digital documents dur...
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Decentralized Privacy-Preserving Proximity Tracing
This document describes and analyzes a system for secure and privacy-pre...
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VoteAgain: A scalable coercion-resistant voting system
The strongest threat model for voting systems considers coercion resista...
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zksk: A Library for Composable Zero-Knowledge Proofs
Zero-knowledge proofs are an essential building block in many privacy-pr...
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Filter Design for Delay-Based Anonymous Communications
In this work, we address the problem of designing delay-based anonymous ...
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Understanding the Effects of Real-World Behavior in Statistical Disclosure Attacks
High-latency anonymous communication systems prevent passive eavesdroppe...
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A Least Squares Approach to the Static Traffic Analysis of High-Latency Anonymous Communication Systems
Mixes, relaying routers that hide the relation between incoming and outg...
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Meet the Family of Statistical Disclosure Attacks
Disclosure attacks aim at revealing communication patterns in anonymous ...
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Encrypted DNS --> Privacy? A Traffic Analysis Perspective
Virtually every connection to an Internet service is preceded by a DNS l...
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Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning
A membership inference attack (MIA) against a machine learning model ena...
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Under the Hood of Membership Inference Attacks on Aggregate Location Time-Series
Aggregate location statistics are used in a number of mobility analytics...
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On (The Lack Of) Location Privacy in Crowdsourcing Applications
Crowdsourcing enables application developers to benefit from large and d...
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Why Johnny Can't Develop Mobile Crowdsourcing Applications with Location Privacy
Mobile crowdsourcing (MCS) relies on users' devices as sensors to perfor...
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Questioning the assumptions behind fairness solutions
In addition to their benefits, optimization systems can have negative ec...
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Evading classifiers in discrete domains with provable optimality guarantees
Security-critical applications such as malware, fraud, or spam detection...
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A Tabula Rasa Approach to Sporadic Location Privacy
Attacks and defenses in the location privacy literature largely consider...
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Tandem: Securing Keys by Using a Central Server While Preserving Privacy
Users' devices, e.g., smartphones or laptops, are typically incapable of...
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POTs: Protective Optimization Technologies
In spite of their many advantages, optimization systems often neglect th...
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Under the Underground: Predicting Private Interactions in Underground Forums
Underground forums where users discuss, buy, and sell illicit services a...
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TARANET: Traffic-Analysis Resistant Anonymity at the NETwork layer
Modern low-latency anonymity systems, no matter whether constructed as a...
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Feature importance scores and lossless feature pruning using Banzhaf power indices
Understanding the influence of features in machine learning is crucial t...
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