  Quantum computing has evolved quickly in recent years and is showing
significant benefits in a variety of fields, especially in the realm of
cybersecurity. The combination of software used to locate the most frequent
hashes and $n$-grams that identify malicious software could greatly benefit
from a quantum algorithm. By loading the table of hashes and $n$-grams into a
quantum computer we can speed 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 simulator. 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 $O(\sqrt{N})$ in the number of table lookups to find the
desired hash values.
