| Title | Mobile APP Personal Information Security Detection and Analysis |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Li, Shuang, Zhang, Meng, Li, Che, Zhou, Yue, Wang, Kanghui, Deng, Yaru |
| Conference Name | 2021 IEEE/ACIS 19th International Conference on Computer and Information Science (ICIS) |
| Keywords | Collaboration, Force, information science, Information security, Manuals, Memory, Mobile app, personal information, policy-based governance, privacy, pubcrawl, Security Policies Analysis, Software Testing, static analysis |
| Abstract | Privacy protection is a vital part of information security. However, the excessive collections and uses of personal information have intensified in the area of mobile apps (applications). To comprehend the current situation of APP personal information security problem of APP, this paper uses a combined approach of static analysis technology, dynamic analysis technology, and manual review to detect and analyze the installed file of mobile apps. 40 mobile apps are detected as experimental samples. The results demonstrate that this combined approach can effectively detect various issues of personal information security problem in mobile apps. Statistics analysis of the experimental results demonstrate that mobile apps have outstanding problems in some aspects of personal information security such as privacy policy, permission application, information collection, data storage, etc. |
| DOI | 10.1109/ICIS51600.2021.9516873 |
| Citation Key | li_mobile_2021 |
Mobile APP Personal Information Security Detection and Analysis