1.北京理工大学计算机学院,北京 100081
2.北京理工大学网络空间安全学院,北京 100081
[ "马文聪 女,1999年出生于安徽省池州市.2021年于北京理工大学获得学士学位.现为北京理工大学计算机学院硕士研究生.主要研究方向为信息安全.E-mail: 3120211066@bit.edu.cn" ]
[ "谭毓安 男,1972年1月出生于重庆巫溪.北京理工大学网络空间安全学院教授.主要研究方向为人工智能安全、系统安全. E-mail: tan2008@bit.edu.cn" ]
[ "冯 硕 女,1997年出生于河北省唐山市.2019年于河北工业大学获得学士学位,2022年于北京理工大学获得硕士学位.主要研究方向为信息安全. E-mail: 17330582191@163.com" ]
[ "刘 璐 女,1992年出生于四川省广安市.2017年于北京理工大学获得硕士学位.现为北京理工大学计算机学院实验师.主要研究方向为信息安全与机器学习. E-mail: liulu@bit.edu.cn" ]
[ "李元章(通讯作者) 男,1978年2月出生于江苏盐城.分别于2001、2004及2015年获得北京理工大学学士、硕士和博士学位.现为北京理工大学计算机学院副教授.主要研究方向为信息系统安全、人工智能安全等. E-mail: popular@bit.edu.cn" ]
收稿:2022-03-28,
修回:2022-07-12,
纸质出版:2023-12-25
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马文聪,谭毓安,冯硕等.基于Android无障碍服务的行为监控[J].电子学报,2023,51(12):3572-3581.
MA Wen-cong,TAN Yu-an,FENG Shuo,et al.Behavior Monitoring Based on Android Accessibility Service[J].ACTA ELECTRONICA SINICA,2023,51(12):3572-3581.
马文聪,谭毓安,冯硕等.基于Android无障碍服务的行为监控[J].电子学报,2023,51(12):3572-3581. DOI: 10.12263/DZXB.20220319.
MA Wen-cong,TAN Yu-an,FENG Shuo,et al.Behavior Monitoring Based on Android Accessibility Service[J].ACTA ELECTRONICA SINICA,2023,51(12):3572-3581. DOI: 10.12263/DZXB.20220319.
用户在手机上的异常行为给社会、企业和个人带来一定的损失和风险.例如用户使用手机违规记录企业的敏感信息、使用手机终端在社交网络上散布违法违规内容和言论等.然而目前尚没有直接运行在终端、对用户本机应用操作进行监控的技术.鉴于目前大部分手机都是Android平台,本文以Android智能手机为研究对象,提出一种基于无障碍服务的用户行为监控技术.用户界面发生变化时,会产生大量基于视图层次结构编写的无障碍事件.本方法筛选出关键的无障碍事件并对其进行遍历,获取界面组件元素、无障碍事件的类型、界面焦点对象等信息,进而判断用户是否存在敏感行为.本方法不依赖于特定的Android版本;通过对无障碍事件进行过滤,提高处理性能;通过调整应用监控范围和监控粒度,保障用户隐私.为了证明本方法的可行性,在真实Android设备上进行测试,可正确监控用户在四种不同应用上的行为.性能测试表明本方法的平均延迟小、CPU(Central Processing Unit)占有率低、内存消耗少,不影响用户正常使用.
The abnormal behavior of users on mobile phones brings certain losses and risks to the country
society
enterprises and individuals. Such as
users record sensitive information of enterprises with the help of mobile phones
or use mobile phones to spread false statements on social networks. However
there is no technology to directly run on the terminal to monitor the user's local application operation. Since most mobile phones are Android platforms
this paper takes Android smart phones as the research object
and proposes a user behavior monitoring technology based on accessibility service. When the phone's interface changes
there will be a large number of accessibility events written based on the view hierarchy. Our method selects the key accessibility events
traverses them
obtains the information on interface component elements
types of accessibility events
interface focus objects and so on
and then judges the user's behavior. Our method does not depend on a specific Android version; improves processing performance by filtering accessibility events; protects users' privacy by adjusting the application monitoring scope and monitoring granularity. In order to prove the feasibility of our method
we experiment on the devices in the physical world and correctly monitor the behavior of users in four different applications. Performance testing shows that our method has low CPU consumption and low average memory occupancy.
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