MalCatcher: Private and Network Data Leakage Behavior-Based Malware Detection on Android
| Autor: | Hsieh, Wei-Yung, 謝維揚 |
|---|---|
| Rok vydání: | 2013 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 More and more people use smartphones in the world. People put more and more their own personal private information into smartphones, so it is important to secure the mobile system, especially Android. Due to the fact that Android is an open-source system, it is easier to develop malwares on Android. In recent years, the number of malwares is dramatically increasing and evolving on Android. We need a effective approach to keep up the speed of malwares’ changes. In this paper, we propose a new dynamic analysis scheme for malware detection on Android, we monitor the app’s behaviors during its execution time and use these behavior information to judge the app whether a malware or not. We also develop a system called MalCatcher to implement our scheme. We add logging function into the Android system source code and compile the modified source code to a system image to build an isolated and monitored environment for Android apps’ execution. Moreover, we have gained a large number of truly malware and normal app to do our experiment and testify our scheme’s effectiveness. Our result show that our scheme can detect malware efficiently. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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