Publications by Carmela González Troncoso

Related publications (42)

Bayes Security: A Not So Average Metric

Carmela González Troncoso, Giovanni Cherubin

Security system designers favor worst-case security metrics, such as those derived from differential privacy (DP), due to the strong guarantees they provide. On the downside, these guarantees result in a high penalty on the system's performance. In this pa ...

IEEE2023

ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging

Carmela González Troncoso, Wouter Lueks, Bogdan Kulynych

The social demand for email end-to-end encryption is barely supported by mainstream service providers. Autocrypt is a new community -driven open specification for e-mail encryption that attempts to respond to this demand. In Autocrypt the encryption keys a ...

ACM2018

Encrypted DNS double right arrow Privacy? A Traffic Analysis Perspective

Carmela González Troncoso, Sandra Deepthy Siby

Virtually every connection to an Internet service is preceded by a DNS lookup. Lookups are performed without any traffic-level protection, thus enabling manipulation, redirection, surveillance, and censorship. To address these issues, large organizations s ...

INTERNET SOC2020

DNS Privacy not so private: the traffic analysis perspective

Carmela González Troncoso, Sandra Deepthy Siby

The Domain Name Service (DNS) is ubiquitous in today’s Internet infrastructure. Almost every connection to an Internet service is preceded by a DNS lookup. A vast majority of DNS queries are sent in plaintext. Thus, they reveal information about the connec ...

2018

On (The Lack Of) Location Privacy in Crowdsourcing Applications

Carmela González Troncoso, Mathias Jacques Jean-Marc Humbert

Crowdsourcing enables application developers to benefit from large and diverse datasets at a low cost. Specifically, mobile crowdsourcing (MCS) leverages users' devices as sensors to perform geo-located data collection. The collection of geo-located data r ...

USENIX ASSOC2019

Bugs in our pockets: the risks of client-side scanning

Carmela González Troncoso

Our increasing reliance on digital technology for personal, economic, and government affairs has made it essential to secure the communications and devices of private citizens, businesses, and governments. This has led to pervasive use of cryptography acro ...

Oxford Univ Press2024

On the (In)security of Peer-to-Peer Decentralized Machine Learning

Carmela González Troncoso, Mathilde Aliénor Raynal, Dario Pasquini

In this work, we carry out the first, in-depth, privacy analysis of Decentralized Learning-a collaborative machine learning framework aimed at addressing the main limitations of federated learning. We introduce a suite of novel attacks for both passive and ...

IEEE COMPUTER SOC2023

PPML '19: Privacy Preserving Machine Learning

Carmela González Troncoso

The area of privacy preserving machine learning has been of growing importance in practice, which has lead to an increased interest in this topic in both academia and industry. We have witnessed this through numerous papers and systems published and develo ...

ACM2019

Protecting Location Privacy: Optimal Strategy against Localization Attacks

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Carmela González Troncoso, Reza Shokri

The mainstream approach to protecting the location-privacy of mobile users in location-based services (LBSs) is to alter the users' actual locations in order to reduce the location information exposed to the service provider. The location obfuscation algor ...

2012

CookieGraph: Understanding and Detecting First-Party Tracking Cookies

Carmela González Troncoso, Sandra Deepthy Siby

As third-party cookie blocking is becoming the norm in mainstream web browsers, advertisers and trackers have started to use first-party cookies for tracking. To understand this phenomenon, we conduct a differential measurement study with versus without th ...

Assoc Computing Machinery2023

Not Yet Another Digital ID: Privacy-Preserving Humanitarian Aid Distribution

Carmela González Troncoso, Wouter Lueks, Boya Wang

Humanitarian aid-distribution programs help bring physical goods to people in need. Traditional paper-based solutions to support aid distribution do not scale to large populations and are hard to secure. Existing digital solutions solve these issues, at th ...

IEEE COMPUTER SOC2023

zksk: A Library for Composable Zero-Knowledge Proofs

Jules Louis Manuel Fasquelle, Carmela González Troncoso, Wouter Lueks, Bogdan Kulynych

Zero-knowledge proofs are an essential building block in many privacy-preserving systems. However, implementing these proofs is tedious and error-prone. In this paper, we present zksk, a well-documented Python library for defining and computing sigma proto ...

Association for Computing Machinery2019

Janus: Safe Biometric Deduplication for Humanitarian Aid Distribution

Carmela González Troncoso, Kasra Edalatnejadkhamene

Humanitarian organizations provide aid to people in need. To use their limited budget efficiently, their distribution processes must ensure that legitimate recipients cannot receive more aid than they are entitled to. Thus, it is essential that recipients ...

Institute of Electrical and Electronics Engineers Inc.2024

Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

Carmela González Troncoso, Dario Pasquini

We introduce the concept of "universal"password model - a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need to access any plaintext passwords from the t ...

Institute of Electrical and Electronics Engineers Inc.2024

Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Carmela González Troncoso

We introduce a new family of prompt injection attacks, termed Neural Exec. Unlike known attacks that rely on handcrafted strings (e.g., Ignore previous instructions and...), we show that it is possible to conceptualize the creation of execution triggers as ...

Association for Computing Machinery2024

Prolonging the Hide-and-Seek Game: Optimal Trajectory Privacy for Location-Based Services

Jean-Yves Le Boudec, Jean-Pierre Hubaux, Carmela González Troncoso, Reza Shokri

Human mobility is highly predictable. Individuals tend to only visit a few locations with high frequency, and to move among them in a certain sequence reflecting their habits and daily routine. This predictability has to be taken into account in the design ...

2014

CrowdNotifier: Decentralized Privacy-Preserving Presence Tracing

Marcel Salathé, Edouard Bugnion, Carmela González Troncoso, Wouter Lueks

There is growing evidence that SARS-CoV-2 can be transmitted beyond close proximity contacts, in particular in closed and crowded environments with insufficient ventilation. To help mitigation efforts, contact tracers need a way to notify those who were pr ...

2021

Reimagining Wearable-Based Digital Contact Tracing: Insights from Kenya and Côte d’Ivoire

Carmela González Troncoso, Kavous Salehzadeh Niksirat

While digital contact tracing has been extensively studied in Western contexts, its relevance and application in Africa remain largely unexplored. This study focuses on Kenya and Côte d’Ivoire to uncover user perceptions and inform the design of culturally ...

ACM2025

WEBGRAPH: Capturing Advertising and Tracking Information Flows for Robust Blocking

Carmela González Troncoso, Sandra Deepthy Siby

Users rely on ad and tracker blocking tools to protect their privacy. Unfortunately, existing ad and tracker blocking tools are susceptible to mutable advertising and tracking content. In this paper, we first demonstrate that a state-of-the-art ad and trac ...

USENIX ASSOC2022

A Low-Cost Privacy-Preserving Digital Wallet for Humanitarian Aid Distribution

Carmela González Troncoso

Humanitarian organizations distribute aid to people affected by armed conflicts or natural disasters. Digitalization has the potential to increase the efficiency and fairness of aid-distribution systems, and recent work by Wang et al. has shown that these ...

IEEE2025