Association Rule Mining for Intrusion Detection System: A SurveyAuthor : D. Selvamani and V. Selvi
Volume 8 No.1 January-March 2019 pp 20-24
Many modern intrusion detection systems are based on data mining and database-centric architecture, where a number of data mining techniques have been found. Among the most popular techniques, association rule mining is one of the important topics in data mining research. This approach determines interesting relationships between large sets of data items. This technique was initially applied to the so-called market basket analysis, which aims at finding regularities in shopping behaviour of customers of supermarkets. In contrast to dataset for market basket analysis, which takes usually hundreds of attributes, network audit databases face tens of attributes. So the typical Apriori algorithm of association rule mining, which needs so many database scans, can be improved, dealing with such characteristics of transaction database. In this paper, a literature survey on the Association Rule Mining has carried out.
Data Mining, Network based Intrusion Detection System, Association Rule Mining, Apriori Algorithm
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