作者: G. V. Nadiammai , M. Hemalatha
DOI: 10.1007/978-3-319-03844-5_9
关键词: Data mining 、 Random forest 、 Machine learning 、 Incremental decision tree 、 Decision stump 、 Anomaly-based intrusion detection system 、 Artificial intelligence 、 Intrusion detection system 、 Computer science 、 C4.5 algorithm 、 Tree (data structure) 、 Random tree
摘要: Intruders attack both commercial and corporate distributed systems successfully. The problem of intruders has become vital. most effective resistance today is the use Intrusion Detection Systems. An intrusion detection system analysis all aspects network activities in order to identify existence unusual patterns that may represent a or made by attempting compromise system. This paper brings an idea applying data mining algorithms Performance various tree based classifiers like Decision Stump, BF Tree, ID3, J48, LAD, Random REP Forest Simple Cart are compared experimental study shows algorithm outperforms than other terms accuracy, specificity sensitivity Time.