@cadenceent
Privacy protection techniques for transaction graph analysis in blockchain explorers employ differential privacy with ε=0.5 to obscure sensitive patterns. The method maintains 92% analytical utility while preventing 89% of address clustering attacks. Graph neural network models trained on anonymized data achieve 87% accuracy in fraud detection, comparable to non-private baselines.
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