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This presentation explores a comprehensive approach to Network Intrusion Detection Systems (NIDS), highlighting their significance and the challenges they face, such as detection accuracy and false positives. It introduces an innovative hybrid AI-powered NIDS methodology, utilizing machine learning models with the NSL-KDD dataset to enhance system performance. The results demonstrate increased detection accuracy and reduced false positives, optimizing real-time performance. The conclusion...