Permission Based in Android Malware Classification

Abstract

Android malware is growing in such an exponential pace which lead out for automated tools that can aid the malware analyst in analysing the behaviours of new malicious applications. This project had proposed clustering in intrusion detection method using hybrid learning approaches combining K-Means clustering and Naïve Bayes classification had been proposed. The result had shown the improved false rate alarm in malware detection.