MALWARE DETECTION AND CLASSIFICATION METHOD AND SYSTEM INCLUDING PATTERN KEY PARTS OF ANDROID APPLICATIONS

摘要

The present invention relates to a technique which patterns (imaging, sounding, etc.) a main part representing an executable code that may contain a malicious code in Android applications, and applies the patterned information to machine learning to diagnose the malicious code, thereby improving the malware detection performance in the Android environment. A system for detecting and classifying Android malware comprises: an inspection area extractor for selectively extracting major parts of the Android application that may contain malicious code; a conversion unit for generating pattern data by patterning the data of the major parts extracted by the inspection area extractor; and a malicious code inspection unit which diagnoses whether pattern data generated by the conversion unit includes malicious code in the pattern data by comparing it with a conventional malicious code pattern.