Hybrid Model for Detecting Android Malware

Android applications are commonly used in smart phones. Nowadays android phone automatically downloads applications without checking that it is a suspicious application or not. Applications downloaded from the internet may be malicious. Malwares can interrupt system operations and can affect the memory usage. The malwares generally appears in the form of signatures, codes, scripts etc. Signatures cannot be found on application before installation process. They are only found during execution. Through this paper we propose hybrid model for the detecting android malwares. Our application automatically detects the malware affected by it by performing analysis .Our application consist of a sandbox which provides an isolated environment. Hybrid model performs two types of analysis, the static analysis and dynamic analysis. Static analysis scans the malware before installing it. It reports the detected malware with the region affected by it. The dynamic analysis is a run time process. Dynamic analysis detects the malware affected by the installed APK (Android Application Package) file. Dynamic analysis is performed on android emulator. It generate corresponding log files, memory status and system performance level.