摘要
为提高人工检测违法违规收集个人信息的效率,基于正则表达式语义分析和机器学习技术,开发了APP(Application)违法违规收集个人信息评估系统。对线上APP进行违法违规检测,生成检测算法和规则,重点解决了隐私政策半自动化获取、APP检测引擎、定制ROM(Read Only Memory)的动态沙箱等技术难点。利用开发的原型系统对各大应用平台上架APP进行常态化技术检测,检测结果表明,该系统大幅提升了违法违规收集个人信息APP综合治理研判效率。
To improve the efficiency of manual detection of illegal and irregular collection of personal information,an APP(Application)personal information evaluation system for illegal and irregular collection is developed based on techniques such as regular expression semantic analysis and machine learning.We conducted illegal and irregular detection on online apps,generated detection algorithms and rules,and focused on solving technical difficulties such as semi automated access to privacy policies,app detection engines,and dynamic sandboxes for custom ROM(Read Only Memory).The developed prototype system is used to conduct regular technical testing on the apps listed on major application platforms.The testing results show that the system significantly improves the efficiency of comprehensive governance and judgment of illegal and irregular collection of personal information apps,and effectively supports the relevant work of higher-level management departments.
作者
李凯
李雨
王乐枭
张晓晴
LI Kai;LI Yu;WANG Lexiao;ZHANG Xiaoqing(Network Secunty Department,Liaoning Branch of National Computer Network Emergency Technology Handling and Coordination Center,Shenyang 110036,China)
出处
《吉林大学学报(信息科学版)》
CAS
2024年第3期537-543,共7页
Journal of Jilin University(Information Science Edition)
基金
国家计算机网络应急技术处理协调中心青年基金资助项目(2021Q56)。