8 research outputs found

    Computational Intelligent Techniques and Similarity Measures for Malware Classification

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    Challenging Anti-virus Through Evolutionary Malware Obfuscation

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    The use of anti-virus software has become something of an act of faith. A recent study showed that more than 80 % of all personal computers have anti-virus software installed. However, the protection mechanisms in place are far less effective than users would expect. Malware analysis is a classical example of cat-and-mouse game: as new anti-virus techniques are developed, malware authors respond with new ones to thwart analysis. Every day, anti-virus companies analyze thousands of malware that has been collected through honeypots, hence they restrict the research to only already existing viruses. This article describes a novel method for malware obfuscation based an evolutionary opcode generator and a special ad-hoc packer. The results can be used by the security industry to test the ability of their system to react to malware mutations
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