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A systematic review of privacy techniques in recommendation systems

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Abstract

The problem of information overload and the necessity for precise information retrieval has led to the extensive use of recommendation systems (RS). However, ensuring the privacy of user information during the recommendation is a major concern. Despite efforts to develop privacy-preserving techniques, a research gap remains in identifying effective and efficient techniques that guarantee privacy. To address this gap, this study presents a systematic review of privacy techniques for recommendation systems published in the past 6 years in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The review categorizes and discusses the most promising privacy techniques and leading research domains in the field of privacy-preserving recommendation systems. Moreover, the study highlights the current challenges faced in this field and identifies open research issues that require further investigation. By presenting a comprehensive analysis of existing work, this study aims to provide a valuable resource for researchers working in the area of privacy-preserving recommendation systems and to promote further research.

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Acknowledgements

The authors will like to appreciate the reviewers for their valuable comments in making the manuscript better. This work is supported by Yibin University, Sichuan Province.

The authors declare that they have no conflict of interest or financial conflicts to disclose.

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  1. International Faculty of Applied Technology, Yibin University, Yibin, 644000, Sichuan Province, China

    Taiwo Blessing Ogunseyi, Cossi Blaise Avoussoukpo & Yiqiang Jiang

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Ogunseyi, T.B., Avoussoukpo, C.B. & Jiang, Y. A systematic review of privacy techniques in recommendation systems. Int. J. Inf. Secur. 22, 1651–1664 (2023). https://doi.org/10.1007/s10207-023-00710-1

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