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The recent advent of play-to-earn (P2E) systems in massively multiplayeronline role-playing games (MMORPGs) has made in-game goods interchangeable withreal-world values more than ever before. The goods in the P2E MMORPGs can bedirectly exchanged with cryptocurrencies such as Bitcoin, Ethereum, or Klaytnvia blockchain networks. Unlike traditional in-game goods, once they had beenwritten to the blockchains, P2E goods cannot be restored by the game operationteams even with chargeback fraud such as payment fraud, cancellation, orrefund. To tackle the problem, we propose a novel chargeback fraud predictionmethod, PU GNN, which leverages graph attention networks with PU loss tocapture both the players' in-game behavior with P2E token transaction patterns.With the adoption of modified GraphSMOTE, the proposed model handles theimbalanced distribution of labels in chargeback fraud datasets. The conductedexperiments on three real-world P2E MMORPG datasets demonstrate that PU GNNachieves superior performances over previously suggested methods.

PU GNN: Chargeback Fraud Detection in P2E MMORPGs via Graph Attention Networks with Imbalanced PU Labels