Personal Privacy Data Protection in Location Recommendation System

Abstract

At present, there are many location-based recommendation algorithms and systems, including location calculation, route calculation, and so on. However, in the general information data publishing, the privacy issues in the published data have not been fully paid attention to and protected. The purpose of this article is to investigate the effectiveness of personal privacy data protection in location recommendation systems. This paper first introduces the basis and importance of research on data security and secrecy, analyses personal privacy issues in data publishing in the era of big data, summarizes the research status in the field of security and secrecy at home and abroad, and introduces the process of data security and the role of users in it. Then, some classic privacy security modules in this field are introduced, and the privacy of data storage security concepts in the current situation mentioned in this paper is analyzed. A geographic location-based privacy protection scheme in mobile cloud is proposed. Privacy analysis, sensitive attribute generalization information analysis, route synthesis analysis and related experiments are performed on the location recommendation system. The experimental results show that the scheme proposed in this paper is more secure and has less loss of data availability.