ANDROID MALWARE DETECTION USING MACHINE LEARNING AND REVERSE ENGINEERING

 Author :  Michal Kedziora

Affiliation :  Wroclaw University of Science and Technology Wroclaw

Country :  Poland

Category :  Computer Science & Information Technology

Volume, Issue, Month, Year :  8, 17, December, 2018

Abstract :

This paper is focused on the issue of malware detection for Android mobile system by Reverse Engineering of java code. The characteristics of malicious software were identified based on a collected set of applications. Total number of 1958 applications where tested (including 996 malware apps). A unique set of features was chosen. Five classification algorithms (Random Forest, SVM, K-NN, Nave Bayes, Logistic Regression) and three attribute selection algorithms were examined in order to choose those that would provide the most effective malware detection.

Keyword :  Malware Detection, Android, Random Forest, SVM, K-NN, Naive Bayes, Logistic Regression 

For More Details :  https://airccj.org/CSCP/vol8/csit89709.pdf