Abstract
In order to identify potential and effective intrusion detection rules, and improve the detection rate of intrusion detection system, this paper combines the concept lattice with intrusion detection technology and proposes a anomaly intrusion detection system based on concept lattice theory. The system first pre-treats those collected data, regulates data and builds concept lattice using the minimal set of attributes which are obtained by attribute reduction. And it analyzes the implication relations between concepts and obtains non-redundant classification rules. The anomaly intrusion detection model based compared with other tests can easily get training data. Experimental results show the model reduces the computation amount to achieve classification, improves the intrusion detection rate and effectively controls the false detection rate.
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