Name
Abstract | ||
|---|---|---|
With the widespread application of Android smartphones, privacy protection plays a crucial role. Android vault application provides content hiding on personal terminals to protect user privacy. However, some vault applications do not achieve real privacy protection, and its camouflage ability can be maliciously used to hide illegal information to avoid forensics. In order to solve these two issues, behavior analysis is conducted to compare three aspects of typical vaults in the third-party market. The conclusions and recommendations were given. Support Vector Machine (SVM) was used to distinguish vault from normal applications. Extensive experiments show that SVM can achieve 93.33% classification accuracy rate. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/978-981-15-7981-3_31 | ICPCSEE (1) |
DocType | Citations | PageRank |
Conference | 1 | 0.38 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nannan Xie | 1 | 2 | 0.73 |
| Hongpeng Bai | 2 | 1 | 0.38 |
| Rui Sun | 3 | 1 | 0.38 |
| Xiaoqiang Di | 4 | 9 | 7.31 |