Exploring Recent Advancements in Machine Learning Techniques for Cyber Security Threat Prediction

MOLAYO FEMI

Authors

MOLAYO FEMI NIGERIA Author

Keywords:

Threat Prediction, Machine Learning, Anomaly Detection, Malware Analysis

Abstract

Recent advancements in machine learning techniques have significantly enhanced the field of cyber security threat prediction. This paper explores the latest developments and innovations in machine learning models applied to predicting cyber security threats. It provides a comprehensive overview of the methodologies, algorithms, and frameworks that have been instrumental in improving threat prediction accuracy and efficiency. The review covers a range of applications, from anomaly detection to malware analysis, highlighting the strengths and limitations of current approaches. By synthesizing recent research findings, this paper aims to contribute to the ongoing discourse on leveraging machine learning for robust cyber security.

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