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A number of works in the field of intrusion detection have been based on Artificial Immune System and Soft Computing. Artificial-Immune-System-based approaches attempt to leverage the adaptability, error tolerance, self-monitoring and distributed nature of Human Immune Systems. The Soft-Computing-based approaches are instrumental in developing fuzzy-rule-based systems for detecting intrusions. They are computationally intensive and apply machine learning (both supervised and unsupervised) techniques to detect the intrusions in a given system. A combination of these two approaches could provide significant advantages for intrusion detection.
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