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    题名: An Incremental Learning Model for Network Intrusion Detection Systems
    作者: 孫士勝
    Sun, Shi-Sheng;Wang, Shang-Te
    贡献者: 資訊系
    关键词: Incremental Learning;Network Intrusion Detection System;NIDS;UNSW-NB15
    日期: 2024-04
    上传时间: 2025-01-07 09:35:48 (UTC+8)
    摘要: With the ever-increasing complexity of Internet security issues, new attack types can be detected every day. The Network Intrusion Detection System (NIDS) can quickly identify and deal with attacks. In this paper, we establish an intrusion detection model suitable for NIDS through incremental learning which can continuously learn the behaviors from new network flows. We utilize the UNSW_NB15 network intrusion dataset, and a portion of the data is used to train the initial model, while the remaining data simulates new network flows. Our proposed model can continuously learn new network flow patterns and adjust parameters without storing original data, while improving the model's training time and maintaining accuracy.
    關聯: 2024 IEEE 10th International Conference on Applied System Innovation, IEEE
    数据类型: conference
    DOI 連結: https://doi.org/10.1109/ICASI60819.2024.10547921
    DOI: 10.1109/ICASI60819.2024.10547921
    显示于类别:[資訊科學系] 會議論文

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