Detecting Threats in IDS using Data Mining Techniques
Keywords:
Data Mining, Knowledge Discovery, Intrusion Detection, Misuse Detection, Anomaly Detection, Clustering, Classification, Association.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
of data can be analyzed and attacks can be detected.
