i ANDROID MALWARE DETECTION MODEL WITH NEGATIVE SELECTION ALGORITHM AND WHALE OPTIMIZATION ALGORITHM

Abstract

This research is Android malware detection model with Negative Selection Algorithm and Whale Optimization Algorithm. Negative selection algorithm has principles and mechanisms to solve problems including the detection of malware. Negative Selection Algorithm with whale optimization was used as optimizer for the selection of best features of android application. The aim is to propose an android malware detection technique for the detection of android malicious applications. The model consists of the basic approach and techniques to achieve good model for the detection of android malicious applications. The research methodology of Data Analysis, which involves validation through experimentation, is employed to achieve this. The results show that the models of selected permission-based features are more accurate than those models without the selection of features. The true positive rate and false alarm rate of selected features are also in better forms than those of classifying features without selection. This research development of Android Malware Detection Model which achieved an improvement in detecting malware with a result of 98.7% performance accuracy.