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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 10
3141-3148

NDP-FD6: multi-classification detection framework for NDP flooding behaviors in IPv6 network

Xia Wenhao1a
Zhang Liancheng2
Guo Yi2
Zhang Hongtao1b
Lin Bin1a
1. a. School of Cyber Science & Engineering, b. Network Management Center, Zhengzhou University, Zhengzhou 450001, China
2. College of Cyberspace Security, Information Engineering University, Zhengzhou 450002, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0633

Abstract

Current researches on NDP flooding behavior detection mainly focus on detecting RA flooding and NS flooding behaviors, and there is insufficient flooding detection for other messages of the NDP protocol. Moreover, traditional threshold rule detection methods suffer from poor dynamics and low accuracy, while most of the AI-based detection methods can only perform binary classification detection, and there are still challenges in performing multi-classification detection. In short, there is a lack of corresponding research in multi-classification flooding detection of all messages of NDP protocol. Therefore, this paper proposed a multi-classification detection framework for NDP protocol flooding behaviors, and proposed a flooding behavior detection method for NDP protocol based on time interval characteristics. The framework constructed the first multiclassification dataset for NDP flooding detection through the processes of traffic collection and data processing, it compared and used 5 machine learning and 5 deep learning algorithms to train the detection model. The experimental results show that the detection accuracy of the XGBOOST algorithm in machine learning can reach 99.18%, and the detection accuracy of the Transformer algorithm in deep learning can reach 98.45%. Compared with the existing detection methods, the accuracy is higher. Meanwhile, the detection framework can detect 9 types of flooding behaviors for all 5 types of messages of NDP protocol and classify the flooding behaviors into multiple types.

Foundation Support

河南省重点研发与推广专项(科技攻关)资助项目(232102210135,212102310989)
河南省高等学校重点科研资助项目(22A520044)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0633
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 10
Section: Technology of Information Security
Pages: 3141-3148
Serial Number: 1001-3695(2024)10-037-3141-08

Publish History

[2024-03-29] Accepted Paper
[2024-10-05] Printed Article

Cite This Article

夏文豪, 张连成, 郭毅, 等. NDP-FD6：一种IPv6网络NDP洪泛行为多分类检测框架 [J]. 计算机应用研究, 2024, 41 (10): 3141-3148. (Xia Wenhao, Zhang Liancheng, Guo Yi, et al. NDP-FD6: multi-classification detection framework for NDP flooding behaviors in IPv6 network [J]. Application Research of Computers, 2024, 41 (10): 3141-3148. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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