A Quantum Algorithm to Locate Unknown Hashgrams
| dc.contributor.author | Allgood, Nicholas R. | |
| dc.contributor.author | Nicholas, Charles | |
| dc.date.accessioned | 2022-11-04T16:22:57Z | |
| dc.date.available | 2022-11-04T16:22:57Z | |
| dc.date.issued | 2022-10-14 | |
| dc.description | Proceedings of the Future Technologies Conference (FTC) 2022, Volume 3 | en_US |
| dc.description.abstract | 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( √ N) in the number of table lookups to find the desired hash values. | en_US |
| dc.description.sponsorship | We extend our thanks to our colleagues Sam Lomonaco and Edward Raff for their comments on an earlier version of this paper. [28]. We also extend our sincere gratitude to Dan Strano for the development and support of the Qrack [5] quantum simulator. | en_US |
| dc.description.uri | https://link.springer.com/chapter/10.1007/978-3-031-18344-7_18 | en_US |
| dc.format.extent | 13 pages | en_US |
| dc.genre | conference papers and proceedings | en_US |
| dc.genre | book chapters | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m2bz5z-pwau | |
| dc.identifier.citation | Allgood, N.R., Nicholas, C.K. (2023). A Quantum Algorithm to Locate Unknown Hashgrams. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 3. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 561. Springer, Cham. https://doi.org/10.1007/978-3-031-18344-7_18 | en_US |
| dc.identifier.uri | https://doi.org/10.1007/978-3-031-18344-7_18 | |
| dc.identifier.uri | http://hdl.handle.net/11603/26276 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Springer | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
| dc.title | A Quantum Algorithm to Locate Unknown Hashgrams | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0001-9494-7139 | en_US |