Systems and methods for detecting obfuscated malware

Abstract

Disclosed are systems, methods and computer program products for efficient and reliable analysis, optimization and detection of obfuscated malware. One disclosed example method for malware detection includes loading an executable software code on a computer system and disassembling the software code into an assembly language or other low-level programming language. The method then proceeds to simplifying complex assembly instructions and constructing a data flow model of the simplified software code. The dependencies and interrelations of code elements of the data flow model are analyzed to identify obfuscated software codes therein. The identified obfuscated codes are then optimized. Based on the results of optimization, determination is made whether the software code is malicious and / or whether further antimalware analysis of the optimized software code is necessary.

Description

technical field [0001] The present invention generally relates to the field of malware detection, and more particularly, to systems and methods for analyzing, optimizing and detecting obfuscated malware. Background technique [0002] The increasing sophistication and rapid proliferation of malicious software (ie, malware) presents an increasing security threat to personal and enterprise computer systems worldwide. In order to prevent the spread of malware such as viruses, worms, Trojan horses, etc., the anti-malware industry has developed various malware detection techniques. These technologies are generally based on the principles of signature matching or heuristic analysis, the signature matching is to compare software codes with known virus code dictionaries, and the heuristic analysis is to simulate and analyze software according to malicious behavior patterns. However, these techniques often fail when applied to obfuscated malware, in which software code is modified (o...

AI Technical Summary

Problems solved by technology

However, these techniques often fail when applied to obfuscated malware, in which software code is modified (or obfuscated) to make analysis difficult

As a result, the detection process becomes extremely inefficient as anti-malware programs fail to detect obfuscated malware, or spend a lot of time and system resources analyzing obfuscated software

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