Title Of Paper:
 
 
Improving the Efficiency of Intrusion Detection Systems Resulted from Combination of Data Mining Method and Machine Learning
Author's Name :  Mostafa Boroumandzadeh, Ali Shaeidi
KeyWords:   Intrusion Detection System, Attack, Data mining, Decision tree.
Pages:  27 -32
Volume: 2
Issue: 12
Year: 2014
Abstract:
 

 

Intrusion detection in a computerized network and the obstacles ahead of it, is the most important challenge in security foundations of these networks for increasing higher efficiency of this detection and it is deniable in fact. However, intrusion detection systems, in addition to their software and hardware models and patterns can be influenced by different attacks in spite of automatizing the processes under processing in the framework of a warning mechanism, and they can change into a trouble making factor for different services or final servers. In This paper, we introduced a combined method of categorized techniques and characteristic reduction to contrast these attacks and by applying intrusion detection method based on data mining. The results showed that there is a comparison between the performances of Random Tree algorithm with j48 algorithm. The accuracy Random Tree algorithm reached 96.05%, a higher percentage than previous methods in this paper.

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