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Abstract: Malicious programs, such as viruses and worms, are frequently related to previous programs through evolutionary relationships. Discovering those relationships and constructing a phylogeny model is expected to be helpful for analyzing new malware and for establishing a principled naming scheme. Matching permutations of code may help build better models in cases where malware evolution does not keep things in the same order. We describe method for constructing phylogeny models that uses... (Update)
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BibTeX entry: (Update)
@misc{ karim-accepted,
author = "Md Enamul Karim",
title = "Accepted to European Research Journal of Computer Virology (2005, to appear)
Malware Phylogeny Generation using Permutations of Code",
url = "citeseer.ist.psu.edu/760958.html" }
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