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Existing Intrusion Detection Systems (IDS) examine all the network features to detect intrusion or misuse patterns. In feature-based intrusion detection, some selected features may found to be redundant, useless or less important than the rest. This paper proposes a category-based selection of effective parameters for intrusion detection using Principal Components Analysis (PCA). In this paper, 32 basic features from TCP/IP header, and 116 derived features from TCP dump are selected in adoi:10.4236/jis.2012.34033 fatcat:nhhpsfsbyfcofauo4jeqzcbgqe