INTRUSION DETECTION IN CYBER SECURITY: MACHINE LEARNING CLASSIFIER PERFORMANCE EVALUATIONID: 1156 Abstract :Industry 4.0 Refers To The Fourth Industrial Revolution, Characterized By The Use Of Smart Technologies, Data Exchange, And Automation In Manufacturing. The Industrial Internet Of Things (IIoT) Is A Crucial Component Of Industry 4.0, Where Devices And Machines Are Connected To The Internet For Enhanced Communication And Data Exchange. As Industries Embrace These Technological Advancements, There Is A Corresponding Increase In The Potential Vulnerabilities To Cyber Threats And Intrusions. Securing The IIoT Environment Becomes Paramount To Ensure The Smooth And Secure Operation Of Industrial Processes. The Need For An Innovative Approach To Combat Intrusion In IIoT Arises From The Critical Nature Of Industrial Processes. Cyber-attacks On IIoT Systems Can Lead To Disruptions In Production, Compromise Of Sensitive Data, And Even Pose Threats To Human Safety. Traditional Security Systems Often Rely On Static And Rule-based Approaches, Which May Not Effectively Adapt To The Dynamic And Sophisticated Nature Of Modern Cyber Threats. Legacy Security Measures Might Lack The Agility And Intelligence Needed To Counter Advanced Persistent Threats And Zero-day Vulnerabilities. Therefore, There Is A Need To Move Beyond Traditional Security Paradigms And Embrace Innovative Approaches That Leverage Cutting-edge Technologies. The Problem At Hand Is The Susceptibility Of IIoT Systems To Cyber Threats And Intrusions. These Threats May Include Unauthorized Access, Data Breaches, Malware Attacks, And Other Forms Of Cyber-attacks That Can Compromise The Integrity, Confidentiality, And Availability Of Industrial Data And Processes. The Challenge Is To Develop A Robust And Proactive Model That Can Detect, Prevent, And Combat Intrusions In Real-time Within The Context Of Industry 4.0. Therefore, This Research Aims To Implement Intrusion Combat Model For IIoT., Where The Significance Of The Proposed Innovative Approach Lies In Its Potential To Enhance The Security Posture Of IIoT Systems In T |
Published:09-6-2025 Issue:Vol. 25 No. 6 (2025) Page Nos:72-81 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to Cite |