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Optimization of IoT Network Security Using Machine Learning

Sam M. K.Sofia ArkhstanHakan Khan
Volume 4

Abstract

Ensuring security in IoT networks is paramount as they become increasingly integrated into critical systems. This paper examines the use of machine learning algorithms to optimize IoT network security. By employing anomaly detection, intrusion prevention systems, and predictive analytics, the proposed framework identifies and mitigates potential threats in real-time. Results show enhanced security and reduced vulnerability to cyber-attacks.

Keywords

IoT Security, Machine Learning, Intrusion Prevention, Anomaly Detection, Cybersecurity

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