Mobile application malicious behavior pattern detection method based on api call graph extraction and recording medium and device for performing the same

Abstract

A mobile application malicious behavior pattern detection method based on Application Programming Interface (API) call graph extraction includes extracting an API Call Graph (ACG) representing an API call flow from benign applications and applications which perform malicious behavior, generating and vectorizing a training dataset for deep learning using the extracted ACG, generating a deep learning algorithm prediction model by training with the vectorized training dataset, extracting ACG features used in the malicious behavior from the generated prediction model and extracting a malicious behavior pattern from an intersection of the malicious applications, and classifying an application which performs malicious behavior through similarity comparison between the extracted malicious behavior pattern and a pattern extracted from the target application. Accordingly, it is possible to detect the malicious behavior itself using the ACG representing an API call flow.