Publications by Mathias Jacques Jean-Marc Humbert

The (Co)-Location Sharing Game

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Kévin Clément Huguenin, Alexandra-Mihaela Olteanu

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends ...

2019

A Survey on Interdependent Privacy

Mathias Jacques Jean-Marc Humbert, Kévin Clément Huguenin, Benjamin Trubert

The privacy of individuals does not only depend on their own actions and data but may also be affected by the privacy decisions and by the data shared by others individuals. This interdependence is an essential aspect of privacy and ignoring it can lead to ...

2019

ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

Mathias Jacques Jean-Marc Humbert

Machine learning (ML) has become a core component of many real-world applications and training data is a key factor that drives current progress. This huge success has led Internet companies to deploy machine learning as a service (MLaaS). Recently, the fi ...

The Internet Society2019

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

Simulating the Large-Scale Erosion of Genomic Privacy Over Time

Mathias Jacques Jean-Marc Humbert, Verena Wolf, Xiaoyu Shen

The dramatically decreasing costs of DNA sequencing have triggered more than a million humans to have their genotypes sequenced. Moreover, these individuals increasingly make their genomic data publicly available, thereby creating privacy threats for thems ...

IEEE COMPUTER SOC2018

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

Towards Usable Checksums: Automating the Integrity Verification ofWeb Downloads for the Masses

Mauro Cherubini, Mathias Jacques Jean-Marc Humbert, Igor Bilogrevic, Bertil Chapuis, Kévin Clément Huguenin, Alexandre Meylan

Internet users can download software for their computers from app stores (e.g., Mac App Store and Windows Store) or from other sources, such as the developers' websites. Most Internet users in the US rely on the latter, according to our representative stud ...

ASSOC COMPUTING MACHINERY2018

Tagvisor: A Privacy Advisor for Sharing Hashtags

Mathias Jacques Jean-Marc Humbert

Hashtag has emerged as a widely used concept of popular culture and campaigns, but its implications on people's privacy have not been investigated so far. In this paper, we present the first systematic analysis of privacy issues induced by hashtags. We con ...

ASSOC COMPUTING MACHINERY2018

Quantifying Interdependent Privacy Risks with Location Data

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Reza Shokri, Kévin Clément Huguenin, Alexandra-Mihaela Olteanu

Co-location information about users is increasingly available online. For instance, mobile users more and more frequently report their co-locations with other users in the messages and in the pictures they post on social networking websites by tagging the ...

Ieee Computer Soc2017

Privacy-enhancing technologies for medical tests using genomic data

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Jacques Rougemont, Amalio Telenti, Jacques Fellay, Erman Ayday, Jean Louis Raisaro

In this invention, we propose privacy-enhancing technologies for medical tests and personalized medicine methods, which utilize patients' genomic data. Assuming the whole genome sequencing is done by a certified institution, we propose to store patients' g ...

2016

De-anonymizing Genomic Databases Using Phenotypic Traits

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Joachim Ludovic Hugonot, Kévin Clément Huguenin, Erman Ayday

People increasingly have their genomes sequenced and some of them share their genomic data online. They do so for various purposes, including to find relatives and to help advance genomic research. An individual's genome carries very sensitive, private inf ...

2015

On Non-cooperative Genomic Privacy

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Amalio Telenti, Erman Ayday

Over the last few years, the vast progress in genome sequencing has highly increased the availability of genomic data. Today, individuals can obtain their digital genomic sequences at reasonable prices from many online service providers. Individuals can st ...

2015

When Others Impinge upon Your Privacy : Interdependent Risks and Protection in a Connected World

Mathias Jacques Jean-Marc Humbert

Privacy is defined as the right to control, edit, manage, and delete information about oneself and decide when, how, and to what extent this information is communicated to others. Therefore, every person should ideally be empowered to manage and protect hi ...

EPFL2015

Reconciling Utility with Privacy in Genomics

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Amalio Telenti, Erman Ayday

Direct-to-consumer genetic testing makes it possible for everyone to learn their genome sequences. In order to contribute to medical research, a growing number of people publish their genomic data on the Web, sometimes under their real identities. However, ...

2014

Addressing the Concerns of the Lacks Family: Quantification of Kin Genomic Privacy

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Amalio Telenti, Erman Ayday

The rapid progress in human-genome sequencing is leading to a high availability of genomic data. This data is notoriously very sensitive and stable in time. It is also highly correlated among relatives. A growing number of genomes are becoming accessible o ...

2013

Nowhere to Hide: Navigating around Privacy in Online Social Networks

Jean-Pierre Hubaux, Matthias Grossglauser, Mathias Jacques Jean-Marc Humbert, Théophile Studer

In this paper, we introduce a navigation privacy attack, where an external adversary attempts to find a target user by exploiting publicly visible attributes of intermediate users. If such an attack is successful, it implies that a user cannot hide simply ...

2013

Collaborative Location Privacy with Rational Users

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Reza Shokri, Francisco De Meneses Neves Ramos Dos Santos

Recent smartphones incorporate embedded GPS devices that enable users to obtain geographic information about their surroundings by providing a location-based service (LBS) with their current coordinates. However, LBS providers collect a significant amount ...

Springer-Verlag Berlin2011

Tracking Games in Mobile Networks

Jean-Pierre Hubaux, Julien Freudiger, Mathias Jacques Jean-Marc Humbert

Users of mobile networks can change their identifiers in regions called mix zones in order to defeat the attempt of third parties to track their location. Mix zones must be deployed carefully in the network to reduce the cost they induce on mobile users an ...

Springer-Verlag New York Inc2010