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논문 리스트

2021
A Study on Security Event Detection in ESM Using Big Data and Deep Learning A Study on Security Event Detection in ESM Using Big Data and Deep Learning
한국인터넷방송통신학회
이상준 외 1명
논문정보
Publisher
The International Journal of Internet, Broadcasting and Communication
Issue Date
2021-08-30
Keywords
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Citation
-
Source
-
Journal Title
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Volume
13
Number
3
Start Page
42
End Page
49
DOI
ISSN
22884920
Abstract
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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