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Active-Passive-Combined Anomaly Detection in Electricity-Carbon Blockchain Trading System Under Limited Bandwidth

  • Tong He
  • , Shilong Zhang
  • , Zisen Xu
  • , Gaofei Ruan
  • , Jin'ao Shang
  • , Zian Luo
  • , Xinyu Yang
  • , Yang Liu
  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In the electricity-carbon blockchain trading system, with the rapid expansion of blockchain technology applications, intrusion events targeting blockchain nodes are becoming increasingly frequent, and security issues are becoming more prominent. The security situation of blockchain systems is increasingly complex and severe. To meet the requirements for real-time and accurate anomaly detection in the electricity-carbon blockchain trading system, this paper proposes an active-passive-combined anomaly detection method. This method comprises two parts: passive anomaly detection and active anomaly detection. Passive anomaly detection collects and analyzes blockchain nodes' network traffic and triggers active anomaly detection when passive anomaly detection identifies an anomaly. In contrast, active anomaly detection collects and evaluates log data from suspicious nodes. This framework can process and analyze large-scale network alerts and host logs under limited bandwidth. Experimental results on real blockchain nodes demonstrate the effectiveness of the proposed method.

源语言英语
主期刊名ICNSC 2024 - 21st International Conference on Networking, Sensing and Control
主期刊副标题Artificial Intelligence for the Next Industrial Revolution
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350365221
DOI
出版状态已出版 - 2024
活动21st International Conference on Networking, Sensing and Control, ICNSC 2024 - Hangzhou, 中国
期限: 18 10月 202420 10月 2024

出版系列

姓名ICNSC 2024 - 21st International Conference on Networking, Sensing and Control: Artificial Intelligence for the Next Industrial Revolution

会议

会议21st International Conference on Networking, Sensing and Control, ICNSC 2024
国家/地区中国
Hangzhou
时期18/10/2420/10/24

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