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In this paper Intrusion Detection Systems (IDSs) are classified according to the techniques applied to processing input data. This process is complex because IDSs are highly coupled in actual implemented systems. Eleven input data processing techniques associated with intrusion detection systems are identified. They are then grouped into more categories. Some approaches are artificially intelligent such as neural networks, expert systems, and agents. Others are computationally based such as Bayesian networks, and fuzzy logic. Finally, some are based on biological concepts such as immune systems and genetics. Characteristics of and systems employing each technique are also mentioned.
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