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Open Access Journal Article

Computational Intelligence Approaches for Cybersecurity Threat Detection

by James Taylor 1,*
1
James Taylor
*
Author to whom correspondence should be addressed.
TASC  2020 2(2):11; https://doi.org/10.69610/j.tasc.20200822
Received: 19 June 2020 / Accepted: 23 July 2020 / Published Online: 22 August 2020
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Abstract

The rapid advancements in technology have brought about significant challenges in the field of cybersecurity, with malicious actors continuously evolving their tactics to breach digital defenses. This paper focuses on computational intelligence approaches to tackle the daunting task of threat detection. It explores the integration of various AI techniques, such as machine learning, data mining, and pattern recognition, to identify patterns indicative of potential cyber threats. The paper discusses the strengths and limitations of each approach, highlighting the importance of feature selection, model training, and robust evaluation metrics. Furthermore, it examines the integration of computational intelligence with traditional cybersecurity tools to enhance the detection of sophisticated attacks, such as zero-day exploits and advanced persistent threats. The paper concludes by emphasizing the need for interdisciplinary research and collaboration to address the dynamic nature of cybersecurity threats and to develop effective computational intelligence-based solutions.

Keywords: Cybersecurity threat detection, Computational intelligence, Machine learning, Data mining, Pattern recognition.;
Copyright: © 2020 by Taylor. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Taylor, J. Computational Intelligence Approaches for Cybersecurity Threat Detection. Transactions on Applied Soft Computing, 2020, 2, 11. https://doi.org/10.69610/j.tasc.20200822
AMA Style
Taylor J. Computational Intelligence Approaches for Cybersecurity Threat Detection. Transactions on Applied Soft Computing; 2020, 2(2):11. https://doi.org/10.69610/j.tasc.20200822
Chicago/Turabian Style
Taylor, James 2020. "Computational Intelligence Approaches for Cybersecurity Threat Detection" Transactions on Applied Soft Computing 2, no.2:11. https://doi.org/10.69610/j.tasc.20200822
APA style
Taylor, J. (2020). Computational Intelligence Approaches for Cybersecurity Threat Detection. Transactions on Applied Soft Computing, 2(2), 11. https://doi.org/10.69610/j.tasc.20200822

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