Algorithm of Mining Fuzzy Associate Rules in Anomaly Detection

An algorithm of mining fuzzy association rules is presented on the basis of improving the classic association rules mining algorithm-Apriori to solve the problem "sharp boundary". In the algorithm, each quantitative attribute is replaced by a fuzzy set and divided into several attributes, which are calculated as separate attributes of database in mining fuzzy associate rules. The process of applying the approach in anomaly detection is discussed in detail. Using experiments on network traffic analysis, the feasibility of applying the mining fuzzy associate rules in intrusion detection is validated.