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What is Hybrid IDS: AI & Rule-Based Threat Detection about?

This thesis presents a hybrid Intrusion Detection System (IDS) that combines machine learning techniques with rule-based algorithms to enhance cybersecurity defenses against evolving cyber threats. The study aims to improve detection accuracy, reduce false positives, and optimize computational efficiency, ultimately providing a scalable and adaptive solution for organizations. Through experimentation and analysis, the research contributes to the advancement of IDS frameworks, fostering a safer digital envir

Author

gzbc14

Language

EN