Research On Android Application Security Detection And Risk Assessment Method

With the rapid development of the mobile Internet,mobile smart terminals have become an integral part of people's work and life.However,with the increasingly widespread application of Android smart terminals in people's daily work and life,various malicious application softwares emerge in an endless stream,causing economic loss and privacy leakage to users.In order to ensure the safety of users using Android smart terminal application software,relevant departments or enterprises widely adopt manual or automated methods for security detection during the application software issuance,and identify and sign the software after security detection for users to download and use.Android application software security detection methods mainly include static detection and dynamic detection.At present,people mainly focus on the problem of inadequate performance and false negative reporting problems.By optimizing the existing and using new detection methods to improve performance and reduce errors.As well as the classification of security risks of application software,are studied to provide help and reference for users to use security software and use software safely.This article conducts in-depth research on Android application software security detection and risk assessment methods.The main research contents and innovations are as follows:1.We propose a secure detection method for Android application software based on permission features.Aiming at the characteristics of Android malicious application family,we design an algorithm DroidFP-Growth for mining frequent itemsets.The algorithm improves the FP-Growth algorithm and effectively reduces the amount of mining computation by setting the maximum support degree and minimum support degree of the permission combination in the malicious application permission item mining process.Experimental results show that the detection method proposed in this paper has better results than other detection methods.2.We propose a dynamic detection method for Android application software security based on system call features.This method takes the system call during the running of the Android application software as the research object,and uses weight comparison and probability statistics to construct the system call feature library of malicious applications and non-malicious applications.When detecting Android application software,determine the nature of the application based on the number of matching features.Selects the optimal threshold for the system call weight and the number of matches by testing.The experimental results show that this method has good effect on application software detection,and with the increase of sample set,the accuracy rate can be further improved.3.We propose a method for risk assessment of Android application software based on chi-square test.Permissions and system call features are used as evaluation factors,and the chi-square test is used to analyze the correlation between the evaluation factors and the application categories and then we can obtain the risk values of the evaluation factors.When evaluating the application software,the risk value of the Android application software is weighted according to the risk value of the evaluation element,and the application software is used to classify the risk,and the user selects the application software and provides a more intuitive reference for adopting the security protection measures against the security risk.Finally,the experiment verifies the rationality and effectiveness of the assessment method.