Recherche

Afficher tous les résultats pour

Accueil

Personne

Carmela González Troncoso

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (42)

Toward a Common Performance and Effectiveness Terminology for Digital Proximity Tracing Applications

Marcel Salathé, Carmela González Troncoso, Wouter Lueks

2021

CrowdNotifier: Decentralized Privacy-Preserving Presence Tracing

Edouard Bugnion, Marcel Salathé, 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

VOTEAGAIN: A scalable coercion-resistant voting system

Carmela González Troncoso, Wouter Lueks

The strongest threat model for voting systems considers coercion resistance: protection against coercers that force voters to modify their votes, or to abstain. Existing remote voting systems either do not provide this property; require expensive operation ...

USENIX ASSOC2020

A research agenda for digital proximity tracing apps

Edouard Bugnion, Marcel Salathé, Carmela González Troncoso, Theresa Stadler

E M H SWISS MEDICAL PUBLISHERS LTD2020

Tandem: Securing Keys by Using a Central Server While Preserving Privacy

Carmela González Troncoso, Wouter Lueks

Users' devices, e.g., smartphones or laptops, are typically incapable of securely storing and processing cryptographic keys. We present Tandem, a novel set of protocols for securing cryptographic keys with support from a central server. Tandem uses one-tim ...

2020

POTs: Protective Optimization Technologies

Bogdan Kulynych, Carmela González Troncoso, Rebekah Jean Overdorf

Algorithmic fairness aims to address the economic, moral, social, and political impact that digital systems have on populations through solutions that can be applied by service providers. Fairness frameworks do so, in part, by mapping these problems to a n ...

ASSOC COMPUTING MACHINERY2020

Early evidence of effectiveness of digital contact tracing for SARS-CoV-2 in Switzerland

Edouard Bugnion, James Richard Larus, Marcel Salathé, Carmela González Troncoso, Wouter Lueks, Mathias Josef Payer, Theresa Stadler, Daniele Antonioli

In the wake of the pandemic of coronavirus disease 2019 (COVID-19), contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Given the rapid and intense spread of SARS-CoV ...

E M H SWISS MEDICAL PUBLISHERS LTD2020

Measuring Membership Privacy on Aggregate Location Time-Series

Carmela González Troncoso, Apostolos Pyrgelis

2020

Encrypted DNS double right arrow Privacy? A Traffic Analysis Perspective

Narseo Vallina Rodriguez, Sandra Deepthy Siby, Carmela González Troncoso

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

DATASHARENETWORK A Decentralized Privacy-Preserving Search Engine for Investigative Journalists

Bruno Thomas, Laurent Girod, Carmela González Troncoso, Wouter Lueks

Investigative journalists collect large numbers of digital documents during their investigations. These documents can greatly benefit other journalists' work. However, many of these documents contain sensitive information. Hence, possessing such documents ...

USENIX ASSOC2020

GenoShare: Supporting Privacy-Informed Decisions for Sharing Individual-Level Genetic Data

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Carmela González Troncoso

One major obstacle to developing precision medicine to its full potential is the privacy concerns related to genomic-data sharing. Even though the academic community has proposed many solutions to protect genomic privacy, these so far have not been adopted ...

IOS PRESS2020

Rethinking Location Privacy for Unknown Mobility Behaviors

Carmela González Troncoso, Simón Oya Diez

Location Privacy-Preserving Mechanisms (LPPMs) in the literature largely consider that users' data available for training wholly characterizes their mobility patterns. Thus, they hardwire this information in their designs and evaluate their privacy propert ...

IEEE COMPUTER SOC2019

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

On (The Lack Of) Location Privacy in Crowdsourcing Applications

Mathias Jacques Jean-Marc Humbert, Carmela González Troncoso

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

zksk: A Library for Composable Zero-Knowledge Proofs

Bogdan Kulynych, Carmela González Troncoso, Wouter Lueks

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

GenoShare: Supporting Privacy-Informed Decisions for Sharing Exact Genomic Data

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Amalio Telenti, Jean Louis Raisaro, Carmela González Troncoso

The academic community has proposed many solutions to address the privacy concerns associated with genomic-data sharing. However, practitioners have not adopted these solutions due to their impact on the data utility. To address this problem, we introduce ...

EPFL infoscience2018

Knock Knock, Who's There? Membership Inference on Aggregate Location Data

Carmela González Troncoso, Apostolos Pyrgelis

Aggregate location data is often used to support smart services and applications, e.g., generating live traffic maps or predicting visits to businesses. In this paper, we present the first study on the feasibility of membership inference attacks on aggrega ...

2018

DNS Privacy not so private: the traffic analysis perspective

Sandra Deepthy Siby, Carmela González Troncoso

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

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

Bogdan Kulynych, Carmela González Troncoso, Wouter Lueks

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

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

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

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

Page 2 sur 3