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Malware is a pervasive problem in distributed computer and network systems. Identification of malware variants provides great benefit in early detection. Control flow has been proposed as a characteristic that can be identified across variants, resulting in flow-graph based malware classification. Static analysis is widely used for the classification but can be ineffective if malware undergoes a code packing transformation to hide its real content. This paper proposes a novel algorithm for constructing a control flow graph signature using the decompilation technique of structuring. Similarity between structured graphs can be quickly determined using string edit distances.
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