Analysis of Current Machine Learning and AI Techniques to Perform Automated Hacking
| dc.contributor.author | Vishnu, Ramakrishnan V. | |
| dc.contributor.other | Rogers, Leonard (Supervisor) | |
| dc.date.accessioned | 2025-05-01T01:51:51Z | |
| dc.date.available | 2025-05-01T01:51:51Z | |
| dc.date.issued | 2021-01-01 | |
| dc.description | Automated hacking is a modern approach to conduct computer hacking with a significantly higher performance rate directly or remotely. Automated hacking is carried out by computer programs that are programmed to analyze the vulnerability of a system(s) and carry out hacking attacks based on the analysis. Automated hacking is considered one of the most sophisticated computer programming areas with high integrity in coding and running platform-independent. In recent years, the advancement of Artificial Intelligence (AI) and machine learning algorithms has influenced many information technology areas. Automated hacking is one such area in which AI and machine learning have shown a drastic improvement in the efficiency and execution power of cyber intrusions with the capability of self-awareness. (As cited in abstract.) | |
| dc.identifier.doi | https://doi.org/10.7939/r3-dxyn-vv49 | |
| dc.language.iso | en | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Hacking | |
| dc.subject | Machine learning | |
| dc.subject | Artificial intelligence | |
| dc.title | Analysis of Current Machine Learning and AI Techniques to Perform Automated Hacking | |
| dc.type | http://purl.org/coar/resource_type/c_93fc | |
| ual.jupiterAccess | http://terms.library.ualberta.ca/public |
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