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Privacy-aware smart city: a case study in collaborative filtering recommender systems

Citation

Zhang, F and Lee, VE and Jin, R and Garg, S and Choo, K-KR and Maasberg, M and Dong, L and Cheng, C, Privacy-aware smart city: a case study in collaborative filtering recommender systems, Journal of Parallel and Distributed Computing, 127 pp. 145-159. ISSN 0743-7315 (2019) [Refereed Article]

Copyright Statement

Copyright 2018 Elsevier Inc.

DOI: doi:10.1016/j.jpdc.2017.12.015

Abstract

Ensuring privacy in recommender systems for smart cities remains a research challenge, and in this paper we study collaborative filtering recommender systems for privacy-aware smart cities. Specifically, we use the rating matrix to establish connections between a privacy-aware smart city and κ-coRating, a novel privacy-preserving rating data publishing model. First, we model privacy concerns in a smart city as the problem of privacy-preserving collaborative filtering recommendation. Then, we introduce κ-coRating to address privacy concerns in published rating matrices, by filling the null ratings with predicted scores. This allows us to mask the original ratings to preserve κ-anonymity-like data privacy, and enhance data utility (quantified using prediction accuracy in this paper). We show that the optimal κ-coRated mapping is an NP-hard problem and design an efficient greedy algorithm to achieve κ-coRating. We then demonstrate the utility of our approach empirically.

Item Details

Item Type:Refereed Article
Keywords:privacy, Security, IoT
Research Division:Information and Computing Sciences
Research Group:Distributed Computing
Research Field:Distributed and Grid Systems
Objective Division:Information and Communication Services
Objective Group:Computer Software and Services
Objective Field:Application Tools and System Utilities
UTAS Author:Garg, S (Dr Saurabh Garg)
ID Code:125154
Year Published:2019
Web of Science® Times Cited:3
Deposited By:Information and Communication Technology
Deposited On:2018-04-03
Last Modified:2019-04-05
Downloads:0

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