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Context-Dependent Privacy-Aware Photo Sharing based on Machine Learning

Publications associées (75)

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Analysis of Beijing 2022 Big Air Venue through data from WeChat Channel & Weibo

Huishu Deng

The Big Air venue of Beijing is constructed in an industrial heritage site named Shougang, under the concept of activating the abandoned area and linking the Olympic venue with public leisure life. As Beijing 2022 has concluded half a year ago and the Shou ...

2022

Data-Aware Privacy-Preserving Machine Learning

Aleksei Triastcyn

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 ...

EPFL2020

Privacy-preserving photo sharing based on blockchain

Touradj Ebrahimi, Pablo Pfister

Sharing photos online has become an extremely popular activity, raising a wide concern on privacy issues related to the shared content. ProShare, a photo-sharing solution developed by Multimedia Signal Processing Group of EPFL addresses some of these priva ...

SPIE-INT SOC OPTICAL ENGINEERING2020

Bayesian Differential Privacy for Machine Learning

Boi Faltings, Aleksei Triastcyn

%0 Conference Paper %T Bayesian Differential Privacy for Machine Learning %A Aleksei Triastcyn %A Boi Faltings %B Proceedings of the 37th International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2020 %E Hal Daumé III %E A ...

2020

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Boi Faltings, Aleksei Triastcyn

This paper considers the problem of enhancing user privacy in common machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples form a generative adversarial network. We propose employing Bayesian ...

2020

Inpainting 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 ...

2019

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

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

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

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