Android malicious behavior detection method based on Bayesian network

Abstract

The invention discloses an Android malicious act detection method based on the Bayesian network.The method specifically comprises the steps of 1, conducting static feature extraction on an Android application training sample; 2, conducting feature processing, and calculating the correlation degree between feature and category with the chi-squared statistic feature selection approach; 3, establishing an Android software malicious act detection model based on the Bayesian network classification algorithm; 4, inputting an APK extraction feature to be detected into a well trained Bayesian network virus detection model, and calculating the posterior probability of the category of the feature; 5, comparing the two data obtained from the step 4 representing the posterior probability that the APK extraction feature to be detected belongs to the virus category and representing the posterior probability that the APK extraction feature to be detected belongs to the normal category respectively, and taking the category with larger posterior probability as the classification result of the application.The method can effectively detect Android malice applications and reduce the learning time of the Bayesian network to a certain degree.

Description

technical field [0001] The invention belongs to the field of Android malicious behavior detection, in particular to a Bayesian network-based Android malicious behavior detection method. Background technique [0002] In recent years, mobile terminal technology has developed very rapidly, and its functions have become more and more powerful. Mobile smart terminal devices have played an increasingly important role in people's lives, and the number of various mobile smart terminal devices has also shown explosive growth. The smart operating systems mainly used in mobile terminals today include Android, IOS, and Windows Phone. Since Android is an open source system, the Android system has quickly become the pre-installed system of major mobile phone manufacturers since its launch. But at the same time, the number of malicious software in the Android system is also showing a rapid growth trend, among which malicious deduction, privacy theft, and resource consumption are the main ...

AI Technical Summary

Problems solved by technology

[0009] Due to the current security situation of the Android platform and the increasing number of viruses, which have brought serious threats to users, it is necessary to develop a safe and efficient detection method

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