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Survey on Intrusion Detection Using Data Mining Methods

Manish Arya, Sanjiv Sharma


The present emerging information growth has made numerous challenges in the data mining. Data mining is the procedure of removing valid, before known, and comprehensive data sets for the future decision making. With the better technology through WWW, the streaming information comes into the picture with its challenges. The data, which alters with time and updates its value, is known as streaming information. As most of the data is streaming in nature, there are numerous challenges we need to face in the security perspective sense. Intrusion detection system (IDS) works within the detecting supposition of the intruders to protect the respective method. The research in mining of data stream and system for intrusion detection has gained high attraction because of the system’s safety measure significance. Algorithms, frameworks and systems that address security issues have been developed over a few years. A present approach of intrusion detection desires detection rate and high accuracy as well as low false alarm rate. We, in brief, outline and compare a tremendous amount of intrusion detection ways, strategies and systems. In addition, we also talk about tools, which can be used by way of network defenders and data sets.

Cite this Article
Manish Arya, Sanjiv Sharma. Survey on Intrusion Detection Using Data Mining Methods. Journal of Advanced Database Management & Systems. 2016; 3(2): 33–43p.


IDS, data mining, clustering, attacks

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