期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：7
语种：English
出版社：Journal of Theoretical and Applied
摘要：Intrusion Detection System has an important task in detecting threats or attacks in the computer networks. Intrusion Detection System (IDS) is a network protection device used to identify and check data packets in network traffic. Snort is free software used to detect attacks and protect computer networks. Snort can only detect misuse attacks, whereas to detect anomaly attacks using Bayes Network, Naive Bayes, Random Tree, LMT and J-48 Classification Method. In this paper, the experimental study uses the KDDCUP 99 dataset and the dataset taken from Campus Network. The main objective of this research is to detect deceptive packets that pass computer network traffic. The steps taken in this study are data preparation, data cleaning, dataset classification, feature extraction, rules snort for detecting, and detecting packet as an attack or normal. The result of the proposed system is an accurate detection rate.
