NDLI: A differential privacy framework for matrix factorization recommender systems

Content Provider	Springer Nature Link
Author	Friedman, Arik Berkovsky, Shlomo Kaafar, Mohamed Ali
Copyright Year	2016
Abstract	Recommender systems rely on personal information about user behavior for the recommendation generation purposes. Thus, they inherently have the potential to hamper user privacy and disclose sensitive information. Several works studied how neighborhood-based recommendation methods can incorporate user privacy protection. However, privacy preserving latent factor models, in particular, those represented by matrix factorization techniques, the state-of-the-art in recommender systems, have received little attention. In this paper, we address the problem of privacy preserving matrix factorization by utilizing differential privacy, a rigorous and provable approach to privacy in statistical databases. We propose a generic framework and evaluate several ways, in which differential privacy can be applied to matrix factorization. By doing so, we specifically address the privacy-accuracy trade-off offered by each of the algorithms. We show that, of all the algorithms considered, input perturbation results in the best recommendation accuracy, while guaranteeing a solid level of privacy protection against attacks that aim to gain knowledge about either specific user ratings or even the existence of these ratings. Our analysis additionally highlights the system aspects that should be addressed when applying differential privacy in practice, and when considering potential privacy preserving solutions.
Starting Page	425
Ending Page	458
Page Count	34
File Format	PDF
ISSN	09241868
Journal	User Modeling and User-Adapted Interaction
Volume Number	26
Issue Number	5
e-ISSN	15731391
Language	English
Publisher	Springer Netherlands
Publisher Date	2016-08-16
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	User Interfaces and Human Computer Interaction Multimedia Information Systems Management of Computing and Information Systems
Content Type	Text
Resource Type	Article
Subject	Education Human-Computer Interaction Computer Science Applications

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