Markov and improved particle swarm optimization-based privacy preservation algorithm for user space geographical location. (22nd June 2020)

• Record Type: Journal Article
• Authors: Chen, Guobin; Li, Shijin
• Is Part Of: European journal of remote sensing. Volume 53(2020)Supplement 1
• Page Start: 31
• Page End: 40
• Publication Date: 2020-06-22
• Subjects: Location-based service -- personal privacy -- HMM-AFMO -- privacy location; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2019.1685911
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: With the development of location-based service, the problem of personal privacy information security is becoming more and more serious. Users' personal privacy information is used without authorization, personal privacy information security is facing various challenges, and personal property security is likely to be violated. Based on HMM model, this paper analyses the location and the location transition probability, and then predicts the location probability by AFMO algorithm. Privacy location information can be predicted by AFMO algorithm, which can improve the accuracy of location prediction. Finally, the experimental results show that the HMM-AFMO algorithm is superior to the HMM model in terms of execution time and effect. In the position prediction, the similarity advantage is obvious, which fully reflects the advantages of the algorithm proposed in this paper.