Application of Artificial Intelligence and Machine Learning Techniques for Network Intrusion Detection and Prevention

Network intrusion detection and prevention is critical for safe computer network security. At the same time, with sophisticated cyber-attacks appearing, traditional intrusion detection methods still need to be improved. Hence, the problem has attracted researchers' attention to solving it using artificial intelligence (AI) and machine learning (ML) techniques. Real-time analysis of these vast amounts of enterprise network data with AI and ML algorithms can expose the patterns and anomalies that suggest malicious activity. Such algorithms can learn from previous attacks and update their models for better detection. Enabling them to detect zero-day attacks that they may have not seen before. In addition, applying artificial intelligence (AI) and machine learning (ML) techniques to prevent network intrusion has become more widespread. Using predictive models, they can survey ongoing network traffic and warn about suspected threats before they can compromise the network. This foresight massively decreases the possibility of attacks being successful and minimizes damage. Conclusion — Using AI and ML Techniques for Network Intrusion Detection & Prevention Provides a more intelligent mechanism for computer network security against intruders.