An efficient privacy-preserving recommender system in wireless networks

• DOI: 10.1007/s11276-022-03130-6
• Publication Date: 2022-11-15T13:04:54Z
• Authors: Junwei Luo; Xun Yi; Fengling Han; Xuechao Yang
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology

Abstract Recommender systems have been widely used for implementing personalised content on many mobile online services to reduce computational overload and preserve wireless data users. The underlying mechanisms building recommender analyse collected from users make recommendations. This poses concerns over the privacy of as both service providers cloud will access. Privacy-preserving protect user information by incorporating various cryptographic prevent accessing data. However, existing works are not practical due use heavy cryptography. In this paper, we propose an efficient privacy-preserving system that takes advantage clustering improve efficiency. Using a secure mechanism, assigned multiple clusters before being fed into recommendation. Our proposed protocols do leak could be identify subject. experiments show our is accurate.