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Open Access

Peer-reviewed

Research Article

Transformer-based comparative multi-view illegal transaction detection

  • Meiling Zhong,

    Roles Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Visualization, Writing – original draft

    Affiliation School of Computer Science and Information Security, Guilin University of Electronic Technology, Guangxi, Guilin, China

    ⨯
  • Yong Wang ,

    Contributed equally to this work with: Yong Wang, Jingke Yan

    Roles Conceptualization, Funding acquisition, Methodology, Resources, Supervision, Writing – review & editing

    592499985@qq.com (YW); 3477443695@qq.com (JY)

    Affiliation School of Computer Science and Information Security, Guilin University of Electronic Technology, Guangxi, Guilin, China

    ⨯
  • Jingke Yan ,

    Contributed equally to this work with: Yong Wang, Jingke Yan

    Roles Conceptualization, Data curation, Formal analysis, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    592499985@qq.com (YW); 3477443695@qq.com (JY)

    Affiliation School of Marine Engineering, Guilin University of Electronic Technology, Beihai, China

    ⨯
  • Yao Cheng,

    Roles Writing – review & editing

    Affiliation State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu, China

    ⨯
  • Peihao Sun

    Roles Data curation

    Affiliation Chinese Academy of Agricultural Sciences, Agricultural information Institute, Beijing, China

    ⨯

Retraction

This article [1] was published in error by PLOS after the authors requested withdrawal. Therefore, PLOS ONE has withdrawn this article [1] and removed the article contents from the journal website. The publisher apologizes for the error.

10 Apr 2023: The PLOS ONE Editors (2023) Withdrawal: Transformer-based comparative multi-view illegal transaction detection. PLOS ONE 18(4): e0283785. https://doi.org/10.1371/journal.pone.0283785 View retraction

Citation: Zhong M, Wang Y, Yan J, Cheng Y, Sun P (2023) Transformer-based comparative multi-view illegal transaction detection. PLoS ONE 18(1): e0276495. https://doi.org/10.1371/journal.pone.0276495

Editor: Barbara Guidi, University of Pisa, ITALY

Received: April 6, 2022; Accepted: October 8, 2022; Published: January 27, 2023

Copyright: © 2023 Zhong et al. This retracted article was originally published as an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. While the article contents were removed from PLOS ONE online at the time of retraction, the Creative Commons Attribution License continues to apply to any existing copies of the article.

Data Availability: The Data Availability Statement was deleted at the time of the article's removal. See the accompanying retraction notice for more information.

Funding: ML Z Grant number is 2022YCXS069, this work is supported by Innovation Project of GUET Graduate Education. Y W Grant number is GCIS202130, this work is supported by Guangxi Key Laboratory of Cryptography and Information Security. Y W Grant number is YF17105, this is supported by Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex System. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.