In today’s digital age, the integration of various fields with the internet and technology has enabled people to meet many issues online, from their basic needs to business, banking and entertainment. However, this digital transformation poses new threats for companies, especially in terms of cyber security. Cyber-attacks can directly harm companies, disrupting systems and damaging their credibility. Despite taking technical measures, companies often encounter weaknesses due to the human factor. This study aims to identify profiles that may cause security vulnerabilities and increase the company’s cybersecurity defense level with appropriate actions. When the results are examined, it is discovered that people with a certain experience range have the same approaches. Using K-means and Mean Shift clustering algorithms, individuals are grouped according to their behaviors and a cyber risk matrix is created for the company, and it is determined which situations these people fall into which risk category. As a result of the data obtained, it is clearly seen that the human factor has emerged as a more important issue than the technical dimension in cyber security.
Primary Language | English |
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Subjects | Machine Learning (Other) |
Journal Section | Research Articles |
Authors | |
Publication Date | March 25, 2025 |
Submission Date | January 30, 2024 |
Acceptance Date | December 9, 2024 |
Published in Issue | Year 2025 Volume: 12 Issue: 1 |
Hittite Journal of Science and Engineering is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).