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| Content Provider | ACM Digital Library |
|---|---|
| Author | Liu, Peng Ren, Chuangang Wu, Dinghao Chen, Kai Huang, Heqing Zhu, Sencun |
| Abstract | In its latest comparison of Android Virus Detectors (AVDs), the independent lab AV-TEST reports that they have around 95% malware detection rate. This only indicates that current AVDs on Android have good malware signature databases. When the AVDs are deployed on the fast-evolving mobile system, their effectiveness should also be measured on their runtime behavior. Therefore, we perform a comprehensive analysis on the design of top 30 AVDs tailored for Android. Our new understanding of the AVDs' design leads us to discover the hazards in adopting AVD solutions for Android, including hazards in malware scan (malScan) mechanisms and the engine update (engineUpdate). First, the malScan mechanisms of all the analyzed AVDs lack comprehensive and continuous scan coverage. To measure the seriousness of the identified hazards, we implement targeted evasions at certain time (e.g., end of the scan) and locations (certain folders) and find that the evasions can work even under the assumption that the AVDs are equipped with "complete" virus definition files. Second, we discover that, during the engineUpdate, the Android system surprisingly nullifies all types of protections of the AVDs and renders the system for a period of high risk. We confirmed the presence of this vulnerable program logic in all versions of Google Android source code and other vendor customized system images. Since AVDs have about 650-1070 million downloads on the Google store, we immediately reported these hazards to AVD vendors across 16 countries. Google also confirmed our discovered hazard in the engineUpdate procedure, so feature enhancements might be included in later versions. Our research sheds the light on the importance of taking the secure and preventive design strategies for AVD or other mission critical apps for fast-evolving mobile-systems. |
| Starting Page | 7 |
| Ending Page | 18 |
| Page Count | 12 |
| File Format | |
| ISBN | 9781450332453 |
| DOI | 10.1145/2714576.2714589 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-04-14 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Vulnerability measurement Malware Mobile Anti-malware |
| Content Type | Text |
| Resource Type | Article |
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