Utilization of Machine Learning in Cybersecurity Threat  Prediction for Proactive Defense and Anomaly Mitigation through  Time-Series and Pattern Learning Techniques

Rohit Ahuja

Utilization of Machine Learning in Cybersecurity Threat Prediction for Proactive Defense and Anomaly Mitigation through Time-Series and Pattern Learning Techniques

Authors

Rohit Ahuja

Keywords:

Machine learning, cybersecurity, threat prediction, anomaly detection, time-series analysis, pattern learning, proactive defense, deep learning.

Abstract

The escalating sophistication of cyber threats necessitates advanced predictivemechanisms to enable proactive defense strategies. This study explores theintegration of machine learning (ML) techniques, particularly time-series analysis and pattern learning, for cybersecurity threat prediction and anomaly mitigation.Employing a mixed-method research design

References

[1] Sidharth Sharma (2023). Ai-driven anomaly detection for advanced threat detection.

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Published

2024-02-06

How to Cite

Rohit Ahuja. (2024). Utilization of Machine Learning in Cybersecurity Threat Prediction for Proactive Defense and Anomaly Mitigation through Time-Series and Pattern Learning Techniques. Journal of Computational Analysis and Applications (JoCAAA), 33(2), 2358–2373. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5747