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Title
Abstract
Introduction
Theoretical Results
Malware Results
Conclusion
References
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Computer Science
Algorithms and Data Structures

A New Burrows Wheeler Transform Markov Distance

Profile image of Charles NicholasCharles Nicholas

2019, arXiv (Cornell University)

https://doi.org/10.48550/ARXIV.1912.13046
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12 pages

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Abstract

Prior work inspired by compression algorithms has described how the Burrows Wheeler Transform can be used to create a distance measure for bioinformatics problems. We describe issues with this approach that were not widely known, and introduce our new Burrows Wheeler Markov Distance (BWMD) as an alternative. The BWMD avoids the shortcomings of earlier efforts, and allows us to tackle problems in variable length DNA sequence clustering.BWMD is also more adaptable to other domains, which we demonstrate on malware classification tasks. Unlike other compression-based distance metrics known to us, BWMD works by embedding sequences into a fixed-length feature vector. This allows us to provide significantly improved clustering performance on larger malware corpora, a weakness of prior methods.

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