DocumentCode
2316332
Title
A heuristic approach for detection of obfuscated malware
Author
Treadwell, Scott ; Zhou, Mian
Author_Institution
Bank of America, Dallas, TX
fYear
2009
fDate
8-11 June 2009
Firstpage
291
Lastpage
299
Abstract
Obfuscated malware has become popular because of pure benefits brought by obfuscation: low cost and readily availability of obfuscation tools accompanied with good result of evading signature based anti-virus detection as well as prevention of reverse engineer from understanding malwares´ true nature. Regardless obfuscation methods, a malware must deobfuscate its core code back to clear executable machine code so that malicious portion will be executed. Thus, to analyze the obfuscation pattern before unpacking provide a chance for us to prevent malware from further execution. In this paper, we propose a heuristic detection approach that targets obfuscated Windows binary files being loaded into memory - prior to execution. We perform a series of static check on binary file´s PE structure for common traces of a packer or obfuscation, and gauge a binary´s maliciousness with a simple risk rating mechanism. As a result, a newly created process, if flagged as possibly malicious by the static screening, will be prevented from further execution. This paper explores the foundation of this research, as well as the testing methodology and current results.
Keywords
invasive software; operating systems (computers); program diagnostics; systems analysis; binary file portable executable structure; executable machine code; obfuscated Window binary file; obfuscated malware detection; obfuscation pattern analysis; risk rating mechanism; static checking; Biology computing; Costs; Cryptography; Employment; Pattern analysis; Payloads; Reverse engineering; Testing; Viruses (medical); Wrapping; Obfuscated; PE header; detection; heuristic; malware;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligence and Security Informatics, 2009. ISI '09. IEEE International Conference on
Conference_Location
Dallas, TX
Print_ISBN
978-1-4244-4171-6
Electronic_ISBN
978-1-4244-4173-0
Type
conf
DOI
10.1109/ISI.2009.5137328
Filename
5137328
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