ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

THE USE OF SUPER VECTOR MACHINE & KEYWORDVECTORS TO DETECT MALWARE ON ANDROID

Abstract

Abstract- The Smartphones have grown in popularity throughout the world as the internet era has progressed. The mostprevalent mobile operating system is Android. The number of malwares targeting smartphones has surged as a result of theincreased use of smartphones. It has become challenging to identify new malware and dangerous software variations. Keycodes such API calls, Android permissions, the common parameters, and the common keywords in Android malware sourcecode are correlated using our method's Keywords Correlation Distance. As a result, the Support Vector Machine (SVM) isdeployed, allowing it to detect both new harmful software and current malware samples. When compared to traditionalapproaches, this method is unique in that it does not rely on the context of the text. An operating system and harmfulsoftware categories are combined in this manner to record malicious software's activities.Keywords: Android, Malware, Keywords Correlation Distance, Super Vector Machine (SVM)

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