An Android Malware Detection Method Based on Chi-Squared Test

The explosive growth of mobile terminals has produced endless malicious applications,bring on great harm to the security of users'privacy and property.To solve this problem,a method based on chi-squared test and Gini impurity increment was proposed for more valuable features extraction and the Naïve Bayes algorithm improvement,so as to improve the estimation accuracy of Android malevolence applications.Test shows that the new features processing method can improve the classification performance of algorithms.At the same time,the improved Naïve Bayes algorithm can achieve higher accuracy than before.