通信学报 ›› 2023, Vol. 44 ›› Issue (4): 124-136.doi: 10.11959/j.issn.1000-436x.2023078
苏新1, 张桂福1, 行鸿彦2, Zenghui Wang3
修回日期:
2023-02-20
出版日期:
2023-04-25
发布日期:
2023-04-01
作者简介:
苏新(1986- ),男,河北霸州人,博士,河海大学教授,主要研究方向为移动通信、边缘/雾计算、智慧海洋等基金资助:
Xin SUN1, Guifu ZHANG1, Hongyan XING2, Wang Zenghui3
Revised:
2023-02-20
Online:
2023-04-25
Published:
2023-04-01
Supported by:
摘要:
针对海洋气象传感网(MMSN)环境下海洋移动终端资源受限和网络流量不平衡导致网络入侵难以被准确检测的问题,提出了一种基于移动边缘计算的MMSN物理架构和一种基于平衡生成对抗网络的入侵检测模型。首先,利用改进的平衡生成对抗网络对不平衡数据进行数据增强。其次,利用基于分组卷积的轻量级网络对入侵数据进行分类。最后,通过计算机仿真证明了所提模型较传统数据增强模型具有更高识别各类攻击的能力,尤其是针对MMSN的少数类样本攻击。
中图分类号:
苏新, 张桂福, 行鸿彦, Zenghui Wang. 基于平衡生成对抗网络的海洋气象传感网入侵检测研究[J]. 通信学报, 2023, 44(4): 124-136.
Xin SUN, Guifu ZHANG, Hongyan XING, Wang Zenghui. Research on intrusion detection for maritime meteorological sensor network based on balancing generative adversarial network[J]. Journal on Communications, 2023, 44(4): 124-136.
表5
NSL-KDD攻击样本扩充的统计评估"
模型 | DoS | Probe | U2R | R2L | |||||||
MED | MMD | MED | MMD | MED | MMD | MED | MMD | ||||
ADASYN | 5.482 5 | 2.531 2 | 0.915 6 | 0.501 9 | 0.163 8 | 0.262 5 | 0.109 0 | 0.224 2 | |||
CWGAN-GP | 0.178 2 | 0.117 3 | 0.006 1 | 0.005 1 | 0.098 2 | 0.189 9 | 0.034 1 | 0.064 4 | |||
BAGAN | 0.546 9 | 0.673 6 | 1.037 0 | 0.561 9 | 0.340 7 | 0.505 0 | 0.052 3 | 0.133 4 | |||
本文模型 | 0.003 7 | 0.009 7 | 0.022 7 | 0.014 1 | 0.062 7 | 0.256 2 | 0.009 7 | 0.019 8 |
表6
CIC-IDS2017数据集攻击样本扩充的统计评估"
模型 | DoS | Port Scan | 暴力破解 | Web Attack | Bot | Infiltration | |||||||||||
MED | MMD | MED | MMD | MED | MMD | MED | MMD | MED | MMD | MED | MMD | ||||||
ADASYN | 1.234 6 | 1.073 2 | 0.044 2 | 1.093 8 | 0.260 6 | 0.626 0 | 0.378 0 | 1.721 7 | 0.403 3 | 0.826 6 | 0.012 9 | 0.039 2 | |||||
CWGAN-GP | 0.001 8 | 0.003 7 | 0.017 4 | 0.267 4 | 0.078 7 | 0.138 5 | 0.143 3 | 2.373 5 | 0.007 9 | 0.060 0 | 4.078 1 | 4.374 4 | |||||
BAGAN | 0.130 5 | 0.157 3 | 0.018 8 | 0.683 8 | 0.012 9 | 0.029 4 | 0.017 0 | 0.101 3 | 0.028 1 | 0.063 7 | 0.263 9 | 0.792 7 | |||||
本文模型 | 0.148 4 | 0.134 4 | 0.001 0 | 0.035 2 | 0.001 4 | 0.004 0 | 0.025 6 | 0.140 5 | 0.016 3 | 0.029 1 | 0.511 9 | 0.759 8 |
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