Protection of Browsing Privacy for Mobile Social Network Users
In order to protect privacy,a mobile social network user browsing privacy protection method is designed based on artificial intelligence technology.This paper aims to set user browsing privacy metrics,calculate the slope of user browsing information trajectory,obtain the slope ratio of user browsing information at different stages,and combine the slope angle to obtain the trajectory function.Based on artificial intelligence technology,a privacy information classification model is established to calculate the similarity between the initiator and ordinary users,determine the probability of correct identification of users,and obtain the classification accuracy of the information classification model.This research designs a privacy protection algorithm for social network users,calculates the number of tracks in the false track area,defines the center position,and obtains the privacy anonymous protection results of mobile social network users.The experimental results show that the privacy protection method has superior performance in privacy protection degree,anonymity delay,algorithm anonymity overhead,etc.
artificial intelligence technologymobile social networknetwork usersbrowsing privacyprivacy protectionprivacy information measurement
NETL
NSTL
万方数据
维普
