Real-Time Detection of Cryptocurrency Mining Behavior

Ke Ye, Meng Shen*, Zhenbo Gao, Liehuang Zhu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

With the rapid development of blockchain, cryptocurrency gains more attention due to its anonymity and decentralization. However, illegal cryptocurrency mining problems, e.g., unauthorized control of victims’ devices or appropriate public resources, become more and more serious. Existing mining detection methods need to be deployed locally and require authorization from administrators, which hardly supervise an entire network segment, as it brings high installation and maintenance costs. To solve this problem, in this paper, we propose a lightweight mining behavior detection method based on traffic analysis, which leverages communication packets in the first n seconds of a flow to achieve a real-time response. The experiment results with real-world datasets prove that the proposed method can achieve 94.04% F1 score using only the first 40 s packets, 98.22% F1 score using the first 120 s packets. Moreover, it can realize unknown cryptomining service discovery for about 96.37% F1 score. Instead of installing antivirus software on the host, the proposed method based on traffic analysis can be deployed at the gateways, which brings convenience for network management.

Original languageEnglish
Title of host publicationBlockchain and Trustworthy Systems - 4th International Conference, BlockSys 2022, Revised Selected Papers
EditorsDavor Svetinovic, Yin Zhang, Xiaoyan Huang, Xiapu Luo, Xingping Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages278-291
Number of pages14
ISBN (Print)9789811980428
DOIs
Publication statusPublished - 2022
Event4th International Conference on Blockchain and Trustworthy Systems, Blocksys 2022 - Chengdu, China
Duration: 4 Aug 20225 Aug 2022

Publication series

NameCommunications in Computer and Information Science
Volume1679 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference4th International Conference on Blockchain and Trustworthy Systems, Blocksys 2022
Country/TerritoryChina
CityChengdu
Period4/08/225/08/22

Keywords

  • Blockchain
  • Mining detection
  • Monero
  • Random forest
  • Traffic analysis

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