Privacy Risks for Multi-Criteria Collaborative Filtering Systems


Yargic A., Bilge A.

26th International Conference on Computer Communication and Networks (ICCCN), Vancouver, Canada, 31 July - 03 August 2017 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icccn.2017.8038509
  • City: Vancouver
  • Country: Canada
  • Keywords: Privacy, Collaborative filtering, Multi-criteria, Privacy violation, RECOMMENDER SYSTEMS, INFORMATION PRIVACY
  • Akdeniz University Affiliated: No

Abstract

In case that individuals feel their privacy is violated while using any recommender system, they might be willing to declare incorrect information or even completely refuse to use such services. To relieve customer concerns, privacy risks that are inherent in the utilization of such systems need to be discussed principally, and service providers should offer privacy preservation mechanisms. Also, there shall be a balance between conflicting goals of accuracy and privacy. In the literature, researchers discuss privacy risks that users are exposed to due to the collection of personal preferences in collaborative recommender systems. However, such studies elaborate on threats arising by submitting a single preference value for items, and they fall short on evaluating privacy risks originating by the collection of preferences in a multi-criteria domain.