년 - 년
A Study on Security Event Detection in ESM Using Big Data and Deep Learning
국제인공지능학회(구 한국인터넷방송통신학회) International Journal of Internet, Broadcasting and Communication Vol.13 No.3 2021.08 pp.42-49
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
As cyber attacks become more intelligent, there is difficulty in detecting advanced attacks in various fields such as industry, defense, and medical care. IPS (Intrusion Prevention System), etc., but the need for centralized integrated management of each security system is increasing. In this paper, we collect big data for intrusion detection and build an intrusion detection platform using deep learning and CNN (Convolutional Neural Networks). In this paper, we design an intelligent big data platform that collects data by observing and analyzing user visit logs and linking with big data. We want to collect big data for intrusion detection and build an intrusion detection platform based on CNN model. In this study, we evaluated the performance of the Intrusion Detection System (IDS) using the KDD99 dataset developed by DARPA in 1998, and the actual attack categories were tested with KDD99's DoS, U2R, and R2L using four probing methods.
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