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Improving Robustness and Accuracy of Ponzi Scheme Detection on Ethereum Using Time-Dependent Features
The contract-code-based approach, while achieving very high accuracy, is not robust: first, the source codes of a majority of contracts on Ethereum are not available, and second, a Ponzi developer can fool a contract-code-based detection model by obfuscating the opcode or inventing a new profit distribution logic that cannot be detected (since these models were trained on existing Ponzi logics only).
Bayesian Optimization with Missing Inputs
In real-world applications, BO often faces a major problem of missing values in inputs.
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