移动端非显式用户身份信息的隐私问题研究

智能设备给人们带来方便的同时也记录了大量使用者的使用习惯、位置、访问内容等隐私信息.文章综合考虑用户行为数据的采集方式,数据处理方式以及存储方式,自主设计用户行为数据的采集系统,并在智能终端设备上采集用户的大量非显式身份信息数据,包括网络流量信息、屏幕状态信息等,通过对这些数据进行处理和分析,发现利用这些非显式的用户身份信息可以有效对用户身份进行识别,并能推测出部分用户间的社会关系.实验表明,基于非显式身份信息数据的研究对保护用户隐私有重要的现实意义和很大的应用价值.

Research on Privacy Analysis of Mobile Implicit User Behavior Data

Smart devices bring convenience to people and also record a large number of user habits, location, access content, and other private information. In this study, considering the way of user behavior data collection, data processing and storage, we design a data acquisition system of user behavior data, and collect a lot of non-explicit identity data on the smart terminal equipment, including network traffic information and screen status information. Through analyzing and processing the data, we found that this non-explicit user identity information can effectively identify the user identity, and can figure out social relationships between the users. The experiment show that, based on the explicit non-identifying information to protect user privacy data has important significance and great value.