Bidirectional fusion heterogeneous graph networks for semi-supervised Bitcoin transaction anomaly detection in dynamic transaction graphs

Bo Xiao, Wei Yin

Open source

DOI: 10.1371/journal.pone.0351051
Published: 2026-06-08
Container: PLOS One
Publisher: Public Library of Science (PLoS)
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1371/journal.pone.0351051,
  title = {Bidirectional fusion heterogeneous graph networks for semi-supervised Bitcoin transaction anomaly detection in dynamic transaction graphs},
  author = {Bo Xiao and Wei Yin},
  year = {2026},
  journal = {PLOS One},
  doi = {10.1371/journal.pone.0351051},
  url = {https://doi.org/10.1371/journal.pone.0351051}
}

RIS

TY  - JOUR
TI  - Bidirectional fusion heterogeneous graph networks for semi-supervised Bitcoin transaction anomaly detection in dynamic transaction graphs
AU  - Bo Xiao
AU  - Wei Yin
PY  - 2026
JO  - PLOS One
DO  - 10.1371/journal.pone.0351051
UR  - https://doi.org/10.1371/journal.pone.0351051
ER  -

APA

Xiao, B., & Yin, W. (2026). Bidirectional fusion heterogeneous graph networks for semi-supervised Bitcoin transaction anomaly detection in dynamic transaction graphs. PLOS One. https://doi.org/10.1371/journal.pone.0351051

Source records

crossref · retrieved 2026-09-25T11:09:27.115Z