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Communication

A Study on Security Event Detection in ESM Using Big Data and Deep Learning

초록

영어

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.

목차

Abstract
1. Introduction
2. Design of intrusion detection system
3. Structure of Intrusion Detection System
3.1 CNN-based intrusion detection module
4. Implement and Result
5. Conclusion
Acknowledgement
References

저자정보

  • Hye-Min Lee MS student., Interdisciplinary Program of Information Security, Chonnam National University
  • Sang-Joon Lee Professor., Interdisciplinary Program of Digital Future Convergence Service, Chonnam National University, Korea

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