This paper proposes a privacy protection and evaluation method for location services based on edge computing environment. By constructing the site service data protection and system evaluation system in the edge computing environment, based on the existing user privacy protection work, the data processing module and service evaluation module are constructed, and the evaluation algorithm is designed. NPE evaluation model and POE evaluation model are designed according to relevant research recommended by IPE. Specifically, in the NPE evaluation model, we regard each user's decision as a group of factors, and propose a method to integrate learning factors. In the poe evaluation model, users' hidden intentions for the next action are understood by unifying metadata information, two time contexts and other different factors. The experiment verifies the effectiveness and feasibility of this method.
翻译:本文根据边际计算环境提出了定位服务的隐私保护和评价方法; 在现有用户隐私保护工作的基础上,在边际计算环境中建立站点服务数据保护和系统评价系统,从而建立了数据处理模块和服务评价模块,并设计了评价算法; NPE 评价模型和POE评价模型是根据IPE建议的相关研究设计的; 具体地说,在NPE评价模型中,我们认为每个用户的决定是一组因素,并提出了综合学习因素的方法; 在插图评价模型中,用户对下一步行动的隐藏意图是通过统一元数据信息、两个时间背景和其他不同因素来理解的; 实验核查这一方法的有效性和可行性。