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A Payment Scheme for Broadcast Multimedia Streams

Publications associées (33)

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Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

EPFL2022

Interdependent and Multi-Subject Privacy: Threats, Analysis and Protection

Alexandra-Mihaela Olteanu

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 ...

EPFL2019

Invited Paper: The Applications of Machine Learning in Privacy Notice and Choice

Hamza Harkous, Kassem Fawaz

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 ...

IEEE2019

Privacy-Enhancing Technologies for Mobile Applications and Services

Thi Van Anh Pham

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 ...

EPFL2019

Towards Scalable Personalization

Rhicheek Patra

The ever-growing amount of online information calls for Personalization. Among the various personalization systems, recommenders have become increasingly popular in recent years. Recommenders typically use collaborative filtering to suggest the most releva ...

EPFL2018

Privacy in Recommender Systems

Mahsa Taziki

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. Recommenders are machine learning approach and are becoming one of the main ways to navigate the Internet. They recommend appropria ...

EPFL2018

Implications of Position in Cryptography

Handan Kilinç Alper

In our daily lives, people or devices frequently need to learn their location for many reasons as some services depend on the absolute location or the proximity. The outcomes of positioning systems can have critical effects e.g., on military, emergency. Th ...

EPFL2018

"If You Can't Beat Them, Join Them'': A Usability Approach to Interdependent Privacy in Cloud Apps

Karl Aberer, Hamza Harkous

Cloud storage services, like Dropbox and Google Drive, have growing ecosystems of 3rd party apps that are designed to work with users’ cloud files. Such apps often request full access to users’ files, including files shared with collaborators. Hence, whene ...

2017

Data-Driven, Personalized Usable Privacy

Hamza Harkous

We live in the "inverse-privacy" world, where service providers derive insights from users' data that the users do not even know about. This has been fueled by the advancements in machine learning technologies, which allowed providers to go beyond the supe ...

EPFL2017

UnLynx: A Decentralized System for Privacy-Conscious Data Sharing

Jean-Pierre Hubaux, Bryan Alexander Ford, Christian Vincent Mouchet, Jean Louis Raisaro, Zhicong Huang, David Jules Froelicher, Joao André Gomes de Sá e Sousa, Patricia Egger

Current solutions for privacy-preserving data sharing among multiple parties either depend on a centralized authority that must be trusted and provides only weakest-link security (e.g., the entity that manages private/secret cryptographic keys), or leverag ...

2017