<![CDATA[A malicious software, or Malware for a short, poses a threat to computer systems, which need to be analyzed, detected, and eliminated. Generally, malware is analyzed in two ways: dynamic malware analysis and static malware analysis. The former collects features dataset during running of the malware, and involves malware APIs, registry activities, file activities, process activities, and network activities based features. The latter collects features dataset prior and without running the malware, and involves Operational Codes (OpCodes) and text based (Bytecodes) features. However, several previous researchers addressed and reviewed malware detection approaches based on various aspects, but none of them addressed and reviewed the approaches merely based on malware OpCodes. Therefore, this paper aims to review Malware Detection Approaches based on OpCodes. The review explores, demonstrates, and compares the existing approaches for detecting malware according to their OpCodes only, and finally presents a comprehensive comparable envisage about them.]]>
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