Detecting and Identifying Insider Threats Based on Advanced Clustering Methods-Reference-Cited by-同舟云学术

Detecting and Identifying Insider Threats Based on Advanced Clustering Methods

Published:2024 Issue: Volume:12 Page:30242-30253
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Nikiforova Oksana¹^ORCID,Romanovs Andrejs¹^ORCID,Zabiniako Vitaly²^ORCID,Kornienko Jurijs²^ORCID

Affiliation:

1. Faculty of Computer Science and Information Technology, Riga Technical University, Riga, Latvia

2. ABC Software Ltd., Riga, Latvia

Funder

“Competence Centre of Information and Communication Technologies” of European Union (EU) Structural Funds, signed between IT Competence Centre and Central Finance and Contracting Agency

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10433132.pdf?arnumber=10433132

Reference33 articles.

1. Application of the Solution for Analysis of IT Systems Users Experience on the Example of Internet Bank Usage

2. Analysis of the Behavior of Company Employees as Users of Information Systems or Tools, Based on Employees Clustering with K-means Algorithm

3. The Information System Security Governance Tasks in Small and Medium Enterprises

4. State of the Art in Cybersecurity and Smart Grid Education

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3. Beyond Information System User Behavior Models: The Power of User Groups in Preventing Insider Attacks;Lecture Notes in Networks and Systems;2024