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Data Mining in Network Security using Intrusion Detection System
Abstract
This paper presents recent trends and practices in data mining to handle the rising risks and threats in the area of Network security. These applications include code detection by mining binary executable, network intrusion detection by mining network traffic, anomaly detection, cyber security and data stream mining. This paper proposes a supervised Learning based Intrusion Detection System (IDS) to identify the intruders, attackers in a network and covers the most significant advances and emerging research issues in the field of data mining in network security.
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References
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