公共网络用户隐私保护位置优化识别仿真

摘要

对公共网络用户隐私保护位置进行准确识别,可以有针对性的对用户位置进行有效保护.用户隐私保护位置识别时,应在用户真实坐标的情况下形成匿名区域,并对构建位置隐私随机k-隐藏集进行检索完成位置识别,但是传统方法主要针对隐私位置特征进行识别,但无法利用用户真实坐标生成匿名区域,导致识别误差大的问题.提出基于随机匿名的公共网络用户隐私保护位置优化识别方法.先在用户请求位置服务时,向匿名服务器发送经过变换后的坐标,匿名服务器可以在未知用户真实坐标的情况下形成匿名区域,利用离散的位置点构建位置隐私随机k-隐藏集,促使彼此之间的网格距离大于阈值,采用私有信息检索协议保障查询结果在检索过程中的隐私性,利用检索结果完成公共网络用户隐私保护位置优化识别.仿真结果表明,公共网络用户隐私保护位置识别稳定性较高,可以有效地完成对公共网络中用户隐私保护位置的识别.%In this paper,we propose an optimization recognition method for position protection of user privacy in public network based on random anonymity.Firstly,the converted coordinate was sent to anonymous server during user requested for position service,and the anonymous server can form anonymity area under the situation of unknown user real coordinate.Then,the discrete position point was used to build the random k-hidden set of position privacy and the grid distance between each other exceeded threshold value.Moreover,we used the retrieval protocol of private information to guarantee the privacy of search result during retrieval process.Finally,we used the retrieval results to complete the optimization recognition on position protection of user privacy in public network.The simulation results show that the method mentioned above has higher recognition stability.It can complete the recognition on protection position of user privacy effectively.