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What is Feature Selection in Intrusion Detection about?

This paper reviews feature selection and ensemble techniques for improving the performance of anomaly-based Intrusion Detection Systems (IDS). It discusses the challenges in selecting relevant data and machine learning algorithms, emphasizing the importance of dimensionality reduction and ensemble methods for enhancing detection accuracy. The review also highlights future research directions and the need for effective models to address evolving security threats.

Author

eko prayitno

Language

EN