移动社交网络用户的浏览隐私保护

Protection of Browsing Privacy for Mobile Social Network Users

为保护用户在社交网络中浏览信息的安全,设计移动社交网络用户浏览隐私保护方法。先设置用户浏览隐私度量标准,计算用户浏览信息轨迹斜率,获得不同阶段用户浏览信息斜率比,再结合斜率夹角,得到轨迹函数。基于人工智能技术建立隐私信息分类模型,计算发起者与普通用户之间的相似性,确定用户被正确识别的概率,获取信息分类模型分类精度。设计社交网络用户浏览隐私保护算法,计算虚假轨迹区域的轨迹数目,定义圆心位置,获取移动社交网络用户的隐私匿名保护结果。实验结果显示,该隐私保护方法在隐私保护度、匿名时延和算法匿名开销等方面均有较高性能。

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.