Network Intrusion Detection Using CNN-based Classification Method

Tzu En Peng, I. Hsien Liu, Jung Shian Li, Chuan Kang Liu

研究成果: Conference contribution

摘要

With the rapid advancement of Artificial Intelligence (AI) in recent years, there has been a growing body of AI-related research in the field of Network Intrusion Detection Systems (NIDSs). In this paper, a network intrusion detection method based on Convolutional Neural Network (CNN) was tested using the KDD Cup 99 dataset. Along with Sigmoid-weighted Linear Unit (SiLU) as the activation function and Stochastic Gradient Descent (SGD) as the optimizer, Batch Normalization (BN) was applied to mitigate internal covariate shift. The evaluation was carried out using performance metrics for the attack classes, which yielded good results for intrusion detection and demonstrated an impressive average accuracy rate of 99.26% after ten epochs, showcasing its promising results in intrusion detection.

原文English
主出版物標題2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023
編輯Jongwoo Park, Ngo Thi Phuong Lan, Sungtaek Lee, Tran Anh Tien, Jongbae Kim
發行者Institute of Electrical and Electronics Engineers Inc.
頁面361-364
頁數4
ISBN(電子)9798350373615
DOIs
出版狀態Published - 2023
事件8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023 - Ho Chi Minh City, Viet Nam
持續時間: 2023 12月 142023 12月 16

出版系列

名字2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

Conference

Conference8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023
國家/地區Viet Nam
城市Ho Chi Minh City
期間23-12-1423-12-16

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦視覺和模式識別
  • 電腦科學應用
  • 資訊系統
  • 資訊系統與管理
  • 建模與模擬

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