Privacy and fairness in recommender systems via adversarial training of user representations

Yehezkel S. Resheff, Yanai Elazar, Moni Shahar, Oren Sar Shalom

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Latent factor models for recommender systems represent users and items as low dimensional vectors. Privacy risks of such systems have previously been studied mostly in the context of recovery of personal information in the form of usage records from the training data. However, the user representations themselves may be used together with external data to recover private user information such as gender and age. In this paper we show that user vectors calculated by a common recommender system can be exploited in this way. We propose the privacy-adversarial framework to eliminate such leakage of private information, and study the trade-off between recommender performance and leakage both theoretically and empirically using a benchmark dataset. An advantage of the proposed method is that it also helps guarantee fairness of results, since all implicit knowledge of a set of attributes is scrubbed from the representations used by the model, and thus can't enter into the decision making. We discuss further applications of this method towards the generation of deeper and more insightful recommendations.

Original languageAmerican English
Title of host publicationICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods
EditorsMaria De Marsico, Gabriella Sanniti di Baja, Ana Fred
PublisherSciTePress
Pages476-482
Number of pages7
ISBN (Electronic)9789897583513
DOIs
StatePublished - 2019
Externally publishedYes
Event8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019 - Prague, Czech Republic
Duration: 19 Feb 201921 Feb 2019

Publication series

NameICPRAM 2019 - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods

Conference

Conference8th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2019
Country/TerritoryCzech Republic
CityPrague
Period19/02/1921/02/19

Bibliographical note

Publisher Copyright:
Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

Keywords

  • Information Leakage
  • Privacy
  • Representations

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