A Quantum Algorithm To Locate Unknown Hashes For Known N-Grams Within A Large Malware Corpus

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2005.02911.pdf (174.79 KB)

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https://arxiv.org/abs/2005.02911

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http://hdl.handle.net/11603/18841

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UMBC Computer Science and Electrical Engineering Department
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2020-05-07

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journal articles preprints
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Nicholas R. Allgood and Charles K. Nicholas, A Quantum Algorithm To Locate Unknown Hashes For Known N-Grams Within A Large Malware Corpus, https://arxiv.org/abs/2005.02911

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Abstract

Quantum computing has evolved quickly in recent years and is showing significant benefits in a variety of fields. Malware analysis is one of those fields that could also take advantage of quantum computing. The combination of software used to locate the most frequent hashes and n-grams between benign and malicious software (KiloGram) and a quantum search algorithm could be beneficial, by loading the table of hashes and n-grams into a quantum computer, and thereby speeding up the process of mapping n-grams to their hashes. The first phase will be to use KiloGram to find the top-k hashes and n-grams for a large malware corpus. From here, the resulting hash table is then loaded into a quantum machine. A quantum search algorithm is then used search among every permutation of the entangled key and value pairs to find the desired hash value. This prevents one from having to re-compute hashes for a set of n-grams, which can take on average O(MN) time, whereas the quantum algorithm could take O(√N) in the number of table lookups to find the desired hash values.