Android software security analysis method based on slice metrics

Abstract

The invention discloses an Android software security analysis method based on slice measurement. The method comprises the steps that data preprocessing is conducted; permission characteristic analysis is conducted and used for calculating characteristic permissions obtained from a permission request file; an Android program is sliced, and slices are subjected to cohesion degree and coupling degree analysis; the permission characteristic analysis result and the cohesion degree and coupling degree analysis result serve as evaluation criteria to judge whether the Android program has a malicious tendency or not; a security evaluation and detection model for the Android program is set up. According to the Android software security analysis method based on slice measurement, for the program slicing result, Androidapk is analyzed from the cohesion degree and coupling degree of a module, the workload of whole apk analysis is reduced, and the working range is narrowed.

Description

technical field [0001] The invention relates to the technical field of software security detection, in particular to an Android software security analysis method based on slice metrics. Background technique [0002] With the continuous development of the computer industry, more and more users choose to use mobile terminals. Among them, the android smart phone is rapidly seizing the smart phone market due to its open source and high cost performance. However, due to the open source nature of the android market, users can download various software freely and for free, and some software with malicious behaviors will inevitably be downloaded. They regard the user's smart terminal as a potential attack target, causing a lot of losses to the user. For example, malicious deductions are generated by sending text messages and making phone calls; unnecessary HTTP requests are generated in the application; when downloading the software, a large amount of other unnecessary software is...

AI Technical Summary

Problems solved by technology

[0006] There are many types of malicious behaviors in malware, including malicious deduction by sending text messages and making phone calls; generating unnecessary HTTP requests in applications; installing additional software without the user's knowledge, etc. These behaviors It will bring unnecessary losses to the user without the user's knowledge

In some cases, these behaviors will not only cause the leakage of user information, but also generate a lot of malicious deductions, which will bring economic losses to users.

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