FORPS: friends-oriented reputation privacy score

Authors:
David Pergament;Armen Aghasaryan;Jean-Gabriel Ganascia;Stéphane Betgé-Brezetz
Affiliations:
Alcatel-Lucent Bell Labs, Nozay, France, Université Pierre et Marie Curie, Paris, France;Alcatel-Lucent Bell Labs, Nozay, France;LIP6 - Université Pierre et Marie Curie, Paris, France;Alcatel-Lucent Bell Labs, Nozay, France
Venue:
Proceedings of the First International Workshop on Security and Privacy Preserving in e-Societies
Year:
2011

Citing 5
Cited 0

Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions

IEEE Transactions on Knowledge and Data Engineering
Persona: an online social network with user-defined privacy

Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Labeled LDA: a supervised topic model for credit attribution in multi-labeled corpora

EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Collaborative data privacy for the web

Proceedings of the 2010 EDBT/ICDT Workshops
A Framework for Computing the Privacy Scores of Users in Online Social Networks

ACM Transactions on Knowledge Discovery from Data (TKDD)

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Friends-Oriented Reputation Privacy Score (FORPS) system provides a smart and simple way to help end-users managing their privacy in a social network. It aims to prevent a non-desirable propagation of personal sensitive data. FORPS built privacy sensitivity profile by understanding what are the category of themes, the category of objects and the behavioral factors that are important to social network users. FORPS takes full advantage of the knowledge available in a social network from the perspective of a given user, in particular extracted from the data accessible via his friends. More precisely, our approach consists in making a deep analysis of the behavior of somebody who would like to establish connection with the given user in order to estimate the risk of potential violation of his privacy.