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Detecting Threats in IDS using Data Mining Techniques


Author : Sukhleen and Gurpreet Kaundal

Pages : 798-801
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Abstract

Achieving security has become one of the most critical factors as more and more sensitive data and information is being maintained and manipulated online. Intrusion Detection System (IDS) is one of the most popular methods which is used to detect malicious activities and maintains the security of the system. IDS can use either anomaly based approach or misuse based approach. In order to detect the malicious activities large amount of data is analyzed. For analyzing data using data mining techniques are best way to achieve the required objective. This paper discusses the various data mining techniques such as clustering, classification and association rules that can be used with IDS so that huge amount f data can be analyzed and attacks can be detected.

Keywords: Data Mining, Knowledge Discovery, Intrusion Detection, Misuse Detection, Anomaly Detection, Clustering,
Classification, Association.

 

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