A Quantum Algorithm To Locate Unknown Hashes For Known N-Grams Within A Large Malware Corpus
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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)<cit.> 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<cit.> 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.
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