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Abitare oltre la pandemia: verso un nuovo habitat domestico

Publications associées (28)

Rethinking 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 SOC2019

Inpainting in Omnidirectional Images for Privacy Protection

Touradj Ebrahimi, Pinar Akyazi, Evgeniy Upenik

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

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

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

MedChain: Accountable and Auditable Data Sharing in Distributed Medical Scenarios

Jean-Pierre Hubaux, Linus Gasser, Jean Louis Raisaro, Bryan Alexander Ford, Juan Ramón Troncoso-Pastoriza

The current trend towards personalized medicine creates an urgent need to share data among different hospitals and health institutions, which endangers the privacy of the data subjects if not done with the appropriate precautions. Conversely, the frequency ...

2019

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

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Karl Aberer, Hamza Harkous, Kassem Fawaz, Rémi Philippe Lebret

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 ASSOC2018

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Jean-Pierre Hubaux, Igor Bilogrevic, Reza Shokri, Kévin Clément Huguenin, Joana Catarina Soares Machado, Stefan Mihaila, Italo Ivan Dacosta Petrocelli

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