| 张师鹏,李永忠.基于三支决策和数据增广的入侵检测算法[J].南京航空航天大学学报,2021,53(5):735-742 |
| 基于三支决策和数据增广的入侵检测算法 |
| Intrusion Detection Algorithm Based on Three-Way Decisions and Data Augmentation |
| 投稿时间：2020-10-25 修订日期：2020-11-07 |
| DOI：10.16356/j.1005-2615.2021.05.010 |
| 中文关键词: 入侵检测 条件生成对抗网络 三支决策 |
| 英文关键词:intrusion detection conditional generative adversarial networks three-way decisions |
| 基金项目:国家自然科学基金（61471182）资助项目；江苏省研究生科研与实践创新计划（KYCX20_3163）资助项目。 |
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| 中文摘要: |
| 针对传统的入侵检测方法在未知攻击上表现不佳、且没有考虑信息不足的情况对于决策的影响的问题，本文提出了一种基于三支决策和数据增广的入侵检测算法CGAN-3WD。算法利用条件生成对抗网络来满足三支决策理论对数据信息的需求。首先基于三支决策理论对网络行为做出决策，将网络行为划分至正域、负域以及边界域中；之后基于条件生成对抗神经网络来完成数据增广，生成新的样本数据，从而为分类器提供更多的信息以支撑分类器将边界域转化为正域或者负域。NSL-KDD数据集被用于本文的实验中，实验证明，本文提出的算法CGAN-3WD在对入侵行为的检测上要优于对比的方法，能够有效地检测出入侵行为。 |
| 英文摘要: |
| Since traditional intrusion detection methods perform poorly on unknown attacks and do not consider the impact of insufficient information on decision-making， an intrusion detection algorithm based on three three-way decisions and data augmentation called CGAN-3WD is proposed. The conditional generative confrontation nets are used to meet the data requirements of the three-way decisions. First， the three-way decisions theory is used to make decisions about network behavior， and it can catagorize network behavior into the positive domain， the negative domain or the boundary domain. Second， new samples are generated by the conditional generative adversarial nets， and the new samples can provide more information for the classifier to put the boundary domain into the positive or the negative domain. Third， the NSL-KDD dataset is used in the experiments. Experiments have proved that the CGAN-3WD model has indeed achieved good performance in intrusion detection， and it can effectively detect intrusions. |
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