Application identification method and device, storage medium and electronic equipment

Abstract

The invention discloses an application identification method and device, a storage medium and electronic equipment, and the method comprises the steps: determining the feature data of a to-be-identified application when the operation of the to-be-identified application is detected; and determining an identification result of the to-be-identified application based on the feature data of the to-be-identified application and a sample database. Therefore, the electronic equipment can perform dynamic identification when the application runs, an additional detection environment does not need to be constructed, the performance loss of the electronic equipment is reduced, the time delay problem between the identification result and the application running is avoided, and the identification efficiency of the application is further improved.

Description

technical field [0001] The present application relates to the technical field of computer security, in particular to an application identification method, device, storage medium and electronic equipment. Background technique [0002] With the popularity of the Android system and smart terminals, more and more Android applications are downloaded and used by users. Many Android applications will obtain users' private information by carrying malicious programs. Commonly used detection methods for Android malicious applications are mainly divided into static detection methods and dynamic detection methods. Taking dynamic detection as an example, a sandbox environment can be installed on the detection terminal , by using applications in a sandbox environment to extract various dynamic behavioral data features, and compare and analyze them with malicious sample features. [0003] However, based on the dynamic detection method mentioned above, it is necessary to arrange a sandbox ...

AI Technical Summary

Problems solved by technology

[0003] However, based on the dynamic detection method mentioned above, it is necessary to arrange a sandbox environment for detection on other terminals to simulate the application running process to obtain various dynamic behavior data characteristics, which is likely to cause performance loss problems such as processor, memory, and power consumption, and This method requires a sandbox environment to simulate the complete running life cycle of the application. Compared with the running of the application, there is a delay problem, which affects the detection experience of the application.

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