Many crimes that are committed in the real world also occur on the internet. These include fraud, Embezzlement, harassment, “stealing” of an identity or stalking. Current signature b a s e d s y s t e m s are inadequate t o tackle t h i s menace. Hence new improved and intelligent systems are in greater demand. In this paper, we propose a system for network intrusion detection using data-mining based techniques for intrusion detection. We use decision tree with entropy function and feature extraction. The IDS is designed to provide the basic detection techniques so as to secure the systems present in the networks that are directly or indirectly connected to the Internet .The experimental results show that our approach provides better performance in terms of accuracy and costthan the ‘Knowledge Development and Data mining’ (KDD) ’99 cup challenge

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Decision Trees Intrusion Detection Data Mining Feature Extraction Entropy function