Humanitarian organizations provide aid to people in need. To use their
l...
Research on adversarial robustness is primarily focused on image and tex...
Humanitarian aid-distribution programs help bring physical goods (e.g., ...
Decentralized Learning (DL) is a peer–to–peer learning approach that all...
Mechanisms used in privacy-preserving machine learning often aim to guar...
We develop the first universal password model – a password model that, o...
Many machine learning problems use data in the tabular domains. Adversar...
Recent privacy protections by browser vendors aim to limit the abuse of
...
We introduce Private Set Matching (PSM) problems, in which a client aims...
In this work, we carry out the first, in-depth, privacy analysis of
Dece...
Website fingerprinting (WF) is a well-know threat to users' web privacy....
Our increasing reliance on digital technology for personal, economic, an...
Millions of web users directly depend on ad and tracker blocking tools t...
In this document, we analyse the potential harms a large-scale deploymen...
Digital proximity tracing (DPT) for Sars-CoV-2 pandemic mitigation is a
...
Synthetic datasets drawn from generative models have been advertised as ...
Security system designers favor worst-case security measures, such as th...
Current day software development relies heavily on the use of service
ar...
Investigative journalists collect large numbers of digital documents dur...
This document describes and analyzes a system for secure and
privacy-pre...
The strongest threat model for voting systems considers coercion resista...
Zero-knowledge proofs are an essential building block in many
privacy-pr...
In this work, we address the problem of designing delay-based anonymous
...
High-latency anonymous communication systems prevent passive eavesdroppe...
Mixes, relaying routers that hide the relation between incoming and outg...
Disclosure attacks aim at revealing communication patterns in anonymous
...
Virtually every connection to an Internet service is preceded by a DNS
l...
A membership inference attack (MIA) against a machine learning model ena...
Aggregate location statistics are used in a number of mobility analytics...
Crowdsourcing enables application developers to benefit from large and
d...
Mobile crowdsourcing (MCS) relies on users' devices as sensors to perfor...
In addition to their benefits, optimization systems can have negative
ec...
Security-critical applications such as malware, fraud, or spam detection...
Attacks and defenses in the location privacy literature largely consider...
Users' devices, e.g., smartphones or laptops, are typically incapable of...
In spite of their many advantages, optimization systems often neglect th...
Underground forums where users discuss, buy, and sell illicit services a...
Modern low-latency anonymity systems, no matter whether constructed as a...
Understanding the influence of features in machine learning is crucial t...