Publication
P3LI5: Practical and confidEntial Lawful Interception on the 5G core
Publications associées (32)
Bridging the gap between theoretical and practical privacy technologies for at-risk populations
With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...
EPFL2023Data Privacy Concerns as a Source of Resistance to Complete Mobile Data Collection Tasks Via a Smartphone App
Smartphones present many interesting opportunities for survey research, particularly through the use of mobile data collection applications (apps). There is still much to learn, however, about how to integrate apps in general population surveys. Recent stu ...
OXFORD UNIV PRESS INC2022Data-Aware Privacy-Preserving Machine Learning
In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...
EPFL2020Privacy-Enhancing Technologies for Mobile Applications and Services
Over a third of the world's population owns a smartphone. As generic computing devices that support a large and heterogeneous collection of mobile applications (apps), smartphones provide a plethora of functionalities and services to billions of users. B ...
EPFL2019Rethinking 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 SOC2019Interdependent and Multi-Subject Privacy: Threats, Analysis and Protection
In Alan Westin's generally accepted definition of privacy, he describes it as an individual's right 'to control, edit, manage, and delete information about them[selves] and decide when, how, and to what extent information is communicated to others.' There ...
EPFL2019Invited Paper: The Applications of Machine Learning in Privacy Notice and Choice
For more than two decades since the rise of the World Wide Web, the "Notice and Choice" framework has been the governing practice for the disclosure of online privacy practices. The emergence of new forms of user interactions, such as voice, and the enforc ...
IEEE2019Inpainting in Omnidirectional Images for Privacy Protection
Touradj Ebrahimi, Evgeniy Upenik, Pinar Akyazi
Privacy protection is drawing more attention with the advances in image processing, visual and social media. Photo sharing is a popular activity, which also brings the concern of regulating permissions associated with shared content. This paper presents a ...
2019Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning
Karl Aberer, Rémi Philippe Lebret, Hamza Harkous, Kassem Fawaz
Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from privacy policies h ...
USENIX ASSOC2018A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins
Jean-Pierre Hubaux, Kévin Clément Huguenin, Igor Bilogrevic, Reza Shokri, Italo Ivan Dacosta Petrocelli, Joana Catarina Soares Machado, Stefan Mihaila
Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they a ...
2018