ENHANCING INTRUSION DETECTION SYSTEMS THROUGH ENSEMBLE LEARNING
Keywords:
Intrusion Detection, Ensemble Learnin, Cybersecurity, Network SecurityAbstract
In today’s rapidly evolving digital world, effective intrusion detection systems are critical for network security. This study looks into the use of machine learning algorithms to improve the effectiveness of intrusion detection. The algorithms are incorporated into various ensemble learning frameworks to enhance detection accuracy and system resilience. The research seeks to identify the most effective approach for precise and efficient intrusion detection by evaluating the performance of the considered models. The findings demonstrate the advantages of ensemble approaches over single models, providing useful insights for developing sophisticated intrusion detection systems. This paper contributes to cybersecurity by doing a thorough evaluation of ensemble learning methods for detecting network intrusions and assuring network security.
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Copyright (c) 2024 Priya P Sajan, Thanseeha C (Author)
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