Permission-based Android malicious software hybrid detection method

Abstract

The invention discloses a permission-based Android malicious software hybrid detection method. The method comprises the following steps: steps one, decompiling an Android application program and obtaining application program application permissions; step two, combining a system setting permission to carry out permission detection on the application program application permissions; dividing all applications to be detected into a kind application set, a malicious application set and a suspicious application set according to the difference of the conditions of the application program application permissions; step three, dynamically acquiring and detecting the behaviors of the application programs in the suspicious application set, collecting interface calling related to sensitive applications, giving vector space representation, and performing application program vectorization; step four, obtaining the detection result of kind application programs meeting safety detection standard through safety detection. Compared with the prior art, the permission-based Android malicious software hybrid detection method integrates two affecting factors of euclidean distance and cosine similarity, and the obtained detection result is more comprehensive and higher in accuracy.

Description

technical field [0001] The invention relates to the fields of computer network and computer security software security detection and mobile terminal security, in particular to the verification of fairness and non-repudiation of a security exchange protocol. Background technique [0002] With the rapid development of mobile communication technology and mobile hardware devices, people rely more and more on smartphones in their daily work and work, and the market share of Android has grown rapidly. As a mainstream mobile smart operating system, Android allows users to download and install third-party applications to meet user needs. However, due to the lack of supervision and management of third-party markets, the number of malware and its variants on the Android platform continues to increase. This phenomenon poses a huge threat to the security of the Android platform. [0003] The rising market share of Android and the rapid growth in the number of Android malware have made...

AI Technical Summary

Problems solved by technology

Permission-based detection methods are fast and efficient in some cases, but the detection effect is not ideal for applications with inconspicuous features; behavior-based detection has the characteristics of large amount of information collection and perfect and accurate analysis methods, but the detection results may be False positives are caused by incomplete information coverage. For applications with obvious features, the detection time is relatively long and the efficiency is not very high.

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