摘要
随着智能手机用户个人信息保护需求增长,移动应用程序(App)收集使用个人信息违规行为的自动化检测技术备受关注。一种利用决策树实现移动应用程序违规行为自动化检测的方法被提出,并进行了实践探索。首先,分析了移动应用程序隐私安全现状和需求,建立了基于决策树的检测框架,该框架有效降低了App检测的误判率,提升了检测效率。其次,在现有技术基础上,引入了新启发式规则,并调整App检测方案的复杂度,增强了模型应对大量移动应用程序检测任务的可行性。最后,提出了决策树在违规行为检测中的改进方向,并对自动化检测技术的未来潜力进行了展望。
With the increasing requirement for personal information protection among smartphone users,automated detection technologies for violations of mobile application(App)collection and use of personal information are attracting much attention.A method for automated detection of mobile application violations using decision trees is proposed and explored in practice.After analyzing the current situation and requirements of mobile application privacy security,a detection framework based on decision tree is established.The decision tree method effectively reduces the rate of misjudgment and improves detection efficiency.Based on the existing technologies,new heuristic rules are introduced and the complexity is adjusted to enhance the feasibility of the model to deal with a large number of mobile application detection tasks.In addition,the improvement directions of decision tree in violation detection are also proposed,and the future potential of automated detection technologies is prospected.
作者
刘陶
张静怡
宋恺
LIU Tao;ZHANG Jingyi;SONG Kai(China Academy of Information and Communications Technology,Beijing 100000,China)
出处
《信息安全与通信保密》
2025年第6期83-92,共10页
Information Security and Communications Privacy
基金
2022年产业技术基础公共服务平台“面向移动互联网应用程序的检测及认证公共服务平台”项目(2022-234-226)。
作者简介
刘陶(1984-),女,博士,高级工程师,主要研究方向为移动应用软件安全、隐私保护、终端安全;张静怡(1995-),女,学士,工程师,主要研究方向为个人信息保护、安全合规;宋恺(1983-),男,硕士,高级工程师,主要研究方向为个人信息保护、网络安全。
