Table · dataset · 2026
HAPV-FEL Transaction Risk Detection Data for IBM AML and SAML-D
Listed in figshare
Description
<p dir="ltr">This dataset package is associated with the study “HAPV-FEL: Historical Consensus Verification and Recoverable Trust for Privacy-Preserving Federated Transaction Risk Detection.” It contains structured CSV representations corresponding to the IBM AML and SAML-D datasets used for cross-institutional transaction risk detection experiments. The data organization follows the experimental setting of 18 federated clients and 120 global training rounds.
Each record includes client and round identifiers, transaction-related attributes such as time, amount, currency and payment type, graph-related account features, binary transaction-risk labels, and fields describing the adversarial federated-learning setting. The experimental protocol considers four attack types: label flipping, sign flipping, scaling, and Gaussian/model poisoning, with a nominal malicious-client ratio of 20%.
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The files are intended to support data inspection, machine-learning experiments, federated transaction-risk analysis, and reproduction of the experimental structure described in the study. Because the manuscript does not publish the complete record-level raw IBM AML and SAML-D data used in the experiments, the CSV records provided here are structured reconstructions based on the reported experimental configuration and should not be interpreted as the original raw transaction records.</p>
Links
Where it is published
- DOI doi.org/10.6084/m9.figshare.33777310.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
Provenance · 1 source records, 17 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33777310 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].anzsrc:group:4611 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:astronomy | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:engineering | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:humanities | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:social-science | mapping · figshare com | connector:figshare_com@1.0.0 | |
| description | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/description |
| license | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/rights |
| publication_date | source · figshare com | connector:figshare_com@1.0.0 | |
| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |