Abstract: The Internet plays a vital role in day-to-day human life activities. It became essential to protect these human activities from unknown internet threats such as Cyber terrorism, Identity theft and many others from the same category. There exist many approaches, which deliver security to some extent, but the ultimate goal of the efficient intrusion detection system is still a challenging task. A data mining based intrusion detection system is proposed in this paper. The proposed intrusion detection system ensures the use of feature extraction and feature selection for data mining and processing. A Packet sniffer based approach works well for network packet tracking, which is used by the proposed intrusion detection system. Data mining along with proper decision support tool can work effectively for intrusion detection. The proposed system works efficient and accurate when tested with KDDCup’99 data.
Keywords: Decision Support Tool, Intrusion Detection, Feature Eradication, Entropy Function, Feature Election
| DOI: 10.17148/IJARCCE.2019.81006