A decision tree-based discovery method for Bitcoin unreachable nodes

被引：0
|
作者：
Li R. [1 ,2 ]
Zhu J. [2 ]
Wu F. [3 ]
Gao J. [3 ]
Xu D. [1 ,3 ]
Zhu L. [1 ]
机构：
[1] School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing
[2] National Computer Network Emergency Response Technical Team Coordination Center of China, Beijing
[3] School of Cyber Security, Changchun University, Changchun
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2024年 / 50卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Bitcoin; cyberspace search engine; decision tree; reachable nodes; unreachable nodes;
D O I：
10.13700/j.bh.1001-5965.2022.0558
中图分类号：
学科分类号：
摘要：
Unreachable nodes refer to nodes that don't accept connection requests in the Bitcoin network, which are difficult to detect and verify. The existing studies mostly focused on the reachable nodes, but less on the unreachable nodes. A new approach is proposed to find the unreachable nodes based on a decision tree model, which can automatically classify unreachable nodes from a large numberof Bitcoin addresses. The results show that the proposed approach got an accuracy of 95.73% and a recall of 91.97% on the experimental dataset. The author applied the approach to the real dataset and verified it by the cyberspace search engines. The proposed approach’s accuracy was 53.75% and the recall was about 76.86%. The distribution of network providers, geographical areas, and the overall number of Unreachable nodes were discussed, which provided technical support for Bitcoin supervision. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
引用
收藏
页码：1861 / 1867
页数：6
相关论文
共 17 条
  • [1] NAKAMOTO S., Bitcoin: A peer-to-peer electronic cash system
  • [2] CAI X Q, DENG Y, ZHANG L, Et al., The principle and core technology of blockchain, Chinese Journal of Computers, 44, 1, pp. 84-131, (2021)
  • [3] Bitcoin P2P network sniffer
  • [4] LI R G, ZHU J W, XU D W, Et al., Bitcoin network measurement and a new approach to infer the topology, China Communications, 19, 10, pp. 169-179, (2022)
  • [5] LI R G, SHEN M, YU H, Et al., A survey on cyberspace search engines, Proceedings of the China Cyber Security Annual Conference, pp. 206-214, (2020)
  • [6] DONET J A, PEREZ-SOLA C, HERRERA-JOANCOMARTI J., The bitcoin P2P network, Proceedings of the International Conference on Financial Cryptography and Data Security, pp. 87-102, (2014)
  • [7] FADHIL M, OWENSON G, ADDA M., A Bitcoin model for evaluation of clustering to improve propagation delay in Bitcoin network, Proceedings of the IEEE International Conference on Computational Science and Engineering and IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposiumon Distributed Computing and Applications for Business Engineering, pp. 468-475, (2016)
  • [8] PARK S, IM S, SEOL Y, Et al., Nodes in the Bitcoin network: Comparative measurement study and survey, IEEE Access, 7, pp. 57009-57022, (2019)
  • [9] BIRYUKOV A, KHOVRATOVICH D, PUSTOGAROV I., Dean-onymisation of clients in Bitcoin P2P network, Proceedings of the ACM SIGSAC Conference on Computer and Communications Security, pp. 15-29, (2014)
  • [10] NEUDECKER T, ANDELFINGER P, HARTENSTEIN H., Timing analysis for inferring the topology of the Bitcoin peer-to-peer network, Proceedings of the International IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress, pp. 358-367, (2016)
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