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Association rule mining is widely used to discover malicious activities by analyzing network traffic data. Apriori algorithm is the most popular association rule mining algorithms, but it has major deficiencies like, requires multiple scan of database, generates large number of frequent item sets repeatedly. This paper presents One Pass Incremental Association Rule Detection algorithm for Network Intrusion Detection System (NIDS). Experimental results are provided to support effectiveness and efficiency of proposed algorithm. Almost every organization stores and manipulates their sensitive information on network. Thus, Intrusion Detection Systems (IDSs) are widely used to protect these networks from intruders. In recent years, data mining is used as important component in IDSs.
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