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The Curious Case of the PDF Converter that Likes Mozart: Dissecting and Mitigating the Privacy Risk of Personal Cloud Apps

Publications associées (52)

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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

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

"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

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

Touradj Ebrahimi, Lin Yuan, Joël Régis Theytaz

Photo privacy has raised a growing concern with the advancements of image analytics, face recognition, and deep learning techniques widely applied on social media. If properly deployed, these powerful techniques can in turn assist people in enhancing their ...

2017

PrivateRide: A Privacy-Enhanced Ride-Hailing Service

Jean-Pierre Hubaux, Taha Hajar, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, Florian Tramèr, Thi Van Anh Pham, Bastien Jacot-Guillarmod

In the past few years, we have witnessed a rise in the popularity of ride-hailing services (RHSs), an online marketplace that enables accredited drivers to use their own cars to drive ride-hailing users. Unlike other transportation services, RHSs raise sig ...

2017

Efficient and Secure Outsourcing of Genomic Data Storage

Jean-Pierre Hubaux, Jean Louis Raisaro, Zhicong Huang, Joao André Gomes de Sá e Sousa

Cloud computing is becoming the preferred solution for efficiently dealing with the increasing amount of genomic data. Yet, outsourcing storage and processing of sensitive data, such as genomic data, comes with important concerns related to privacy and sec ...

Cryptology ePrint Archive: Report 2017/2282017

Data-Driven Privacy Indicators

Karl Aberer, Hamza Harkous, Rameez Rahman

Third party applications work on top of existing platforms that host users’ data. Although these apps access this data to provide users with specific services, they can also use it for monetization or profiling purposes. In practice, there is a significant ...

2016

PriBots: Conversational Privacy with Chatbots

Karl Aberer, Hamza Harkous, Kassem Fawaz

Traditional mechanisms for delivering notice and enabling choice have so far failed to protect users’ privacy. Users are continuously frustrated by complex privacy policies, unreachable privacy settings, and a multitude of emerging standards. The miniaturi ...

2016

Context and Semantic Aware Location Privacy

Berker Agir

With ever-increasing computational power, and improved sensing and communication capabilities, smart devices have altered and enhanced the way we process, perceive and interact with information. Personal and contextual data is tracked and stored extensivel ...

EPFL2016