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Malware creators have been getting their way for too long now. String-basedsimilarity measures can leverage ground truth in a scalable way and can operateat a level of abstraction that is difficult to combat from the code level. Weintroduce ITect, a scalable approach to malware similarity detection based oninformation theory. ITect targets file entropy patterns in different ways toachieve 100% precision with 90% accuracy but it could target 100% recallinstead. It outperforms VirusTotal for precision and accuracy on combinedKaggle and VirusShare malware.

ITect: Scalable Information Theoretic Similarity for Malware Detection