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Privacy 2.0?

2008
Le phénomène du « web 2.0 » représente un défi majeur pour la protection de la vie privée et des données à caractère personnel. Cet article a pour but d'offrir un panorama des risques actuels et à venir dans le cadre des « réseaux sociaux ». Afin de contribuer à la définition de réponses adaptées, il situe le « web 2.0 » dans le contexte de la ...
Gonzalez Fuster, Gloria, Gutwirth, Serge
openaire   +4 more sources

Data Privacy

2011
In today's globally interconnected society, a huge amount of data about individuals is collected, processed, and disseminated. Data collections often contain sensitive personally identifiable information that need to be adequately protected against improper disclosure.
M. Bezzi   +5 more
openaire   +1 more source

Patient Privacy

Journal of Audiovisual Media in Medicine, 2004
As part of the Institute of Medical Illustrators' (IMI) scheme for continuing professional development (CPD), worksheets will be published at regular intervals in this Journal. These are designed to provide the members of IMI with a structured CPD activity that offers one way to earn credits.
openaire   +2 more sources

Privacy

Professional Ethics, A Multidisciplinary Journal, 1994
Charles, Culver   +4 more
openaire   +2 more sources

Practical Secure Aggregation for Privacy-Preserving Machine Learning

IACR Cryptology ePrint Archive, 2017
Keith Bonawitz   +8 more
semanticscholar   +1 more source

Differential Privacy

International Colloquium on Automata, Languages and Programming, 2006
C. Dwork
semanticscholar   +1 more source

Differential Privacy: A Survey of Results

Theory and Applications of Models of Computation, 2008
C. Dwork
semanticscholar   +1 more source

Personal privacy vs population privacy

Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011
Over the last decade great strides have been made in developing techniques to compute functions privately. In particular, Differential Privacy gives strong promises about conclusions that can be drawn about an individual. In contrast, various syntactic methods for providing privacy (criteria such as k-anonymity and l-diversity) have been criticized for
openaire   +1 more source

SecureML: A System for Scalable Privacy-Preserving Machine Learning

IEEE Symposium on Security and Privacy, 2017
Payman Mohassel, Yupeng Zhang
semanticscholar   +1 more source

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