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#fraud-detection

2 curated events
papersTODAY 04:00 UTC

Graph-Transformer Fraud Detection with Self-Supervised Pretraining and Conformal Risk Control

A new arXiv paper introduces GTFD, a graph-transformer approach for spotting fraud in corporate transaction networks. The method combines self-supervised pretraining with conformal risk control to handle coordinated fraud that rule-based systems and per-transaction models miss. It is positioned as an improvement over classical models that analyze each transaction in isolation.

fraud-detection/graph-neural-networks/self-supervised/arxiv
papersSEP 12 04:00 UTC

DeFiFusion: Detecting DeFi Price Manipulation via Transactions and Smart Contracts

A new arXiv paper introduces DeFiFusion, a method that merges on-chain transaction event data with smart contract code analysis to spot price manipulation in decentralized finance. The authors argue that studying market activity and contract logic separately misses attacks that exploit the interaction between the two. The approach is framed as a combined detection framework rather than a deployed product.

defi/blockchain/security/fraud-detection