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Android Malware Detection
Malware is one of the major issues regarding the operating framework or in the software world. The android framework is also going through the same issues. We have seen other Signature based malware location strategies were utilized to recognize malware. Yet, the strategies couldn't recognize obscure malware. In spite of various discovery and analysis procedures are there, the discovery accuracy of new malware is as yet a crucial issue. In this paper, we study and feature the current identification and analysis techniques utilized for the android malicious code. Along with contemplating, we propose Machine learning algorithms that will be utilized to analyze such malware and also we will do semantic analysis. We will be having a data set of authorizations for malicious applications. Which will be compared with the consents extracted from the application which we want to analyze. Eventually, the client will actually want to perceive how much malicious authorization is there in the application and also we analyze the application through remarks.
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