Carmela González Troncoso

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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 ...

Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that synthetic data drawn from generative models preserves the stat ...

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 ...

Homomorphic encryption has become a practical solution for protecting the privacy of computations on sensitive data. However, existing homomorphic encryption pipelines do not guarantee the correctness of the computation result in the presence of a maliciou ...

We introduce Helium, a novel framework that supports scalable secure multiparty computation (MPC) for lightweight participants and tolerates churn. Helium relies on multiparty homomorphic encryption (MHE) as its core building block. While MHE schemes have ...

Humanitarian Organizations assist the most vulnerable populations in extremely challenging circumstances. For reasons of efficiency, accountability, and out of a desire to help as many people as possible, Humanitarian Organizations increasingly rely on dig ...

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 ...

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 ...

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 ...

Multiparty fully homomorphic encryption (MFHE) schemes enable multiple parties to efficiently compute functions on their sensitive data while retaining confidentiality. However, existing MFHE schemes guarantee data confidentiality and the correctness of th ...

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 ...

The rapidly growing demand to share data more openly creates a need for secure and privacy-preserving sharing technologies. However, there are multiple challenges associated with the development of a universal privacy-preserving data sharing mechanism, and ...

Homomorphic encryption has become a promising solution for protecting the privacy of computations on sensitive data. However, existing homomorphic encryption pipelines do not guarantee the correctness of the computation result in the presence of a maliciou ...

Carmela González Troncoso

Chattez avec Graph Search

Rethinking Location Privacy for Unknown Mobility Behaviors

Deploying Decentralized, Privacy-Preserving Proximity Tracing

Synthetic Data - Anonymisation Groundhog Day

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

VERITAS: Plaintext Encoders for Practical Verifiable Homomorphic Encryption

Helium: Scalable MPC among Lightweight Participants and under Churn

Designing for data protection

POTs: Protective Optimization Technologies

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

VOTEAGAIN: A scalable coercion-resistant voting system

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

PELTA - Shielding Multiparty-FHE against Malicious Adversaries

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

A research agenda for digital proximity tracing apps

Why the search for a privacy-preserving data sharing mechanism is failing

Measuring Membership Privacy on Aggregate Location Time-Series

Poster: Verifiable Encodings for Maliciously-Secure Homomorphic Encryption Evaluation