Addendum to: Determining the Cyber Risk Matrix and Actions Created by Company Employees with Machine Learning

The original article was published on March 25, 2025. https://dergipark.org.tr/en/pub/hjse/article/1428607

Erratum Note

Following the publication of this work, it has come to our attention that the original survey instrument and the formal ethics committee approval documentation were not appended to the final publication. This addendum serves to ensure full transparency of the research methodology and to meet contemporary data-sharing standards.

Abstract

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.

Keywords

• Security
• Machine Learning
• Cyber Risk Matrix
• Human Factor
• Cyber Security Awareness

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