Sciweavers

Share
IEEEARES
2008
IEEE

Experimental Demonstration of a Hybrid Privacy-Preserving Recommender System

9 years 7 months ago
Experimental Demonstration of a Hybrid Privacy-Preserving Recommender System
Recommender systems enable merchants to assist customers in finding products that best satisfy their needs. Unfortunately, current recommender systems suffer from various privacy-protection vulnerabilities. We report on the first experimental realization of a theoretical framework called ALAMBIC, which we had previously put forth to protect the privacy of customers and the commercial interests of merchants. Our system is a hybrid recommender that combines content-based, demographic and collaborative filtering techniques. The originality of our approach is to split customer data between the merchant and a semitrusted third party, so that neither can derive sensitive information from their share alone. Therefore, the system can only be subverted by a coalition between these two parties. Experimental results confirm that the performance and user-friendliness of the application need not suffer from the adoption of such privacy-protection solutions. Furthermore, user testing of our pro...
Esma Aïmeur, Gilles Brassard, José Man
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IEEEARES
Authors Esma Aïmeur, Gilles Brassard, José Manuel Fernandez, Flavien Serge Mani Onana, Zbigniew Rakowski
Comments (0)
books