TL;DR
This paper proposes a graph-based system using transaction proximity and easily attainable identities to prevent blockchain fraud, balancing privacy and security without restricting access.
Contribution
It introduces a novel approach leveraging transaction graph analysis and EAI concepts to enhance fraud prevention while preserving blockchain openness.
Findings
56% of large USDC wallets are EAIs
88% are within one hop of an EAI
83% of exploiter addresses are not EAIs
Abstract
This paper introduces a fraud-deterrent access validation system for public blockchains, leveraging two complementary concepts: "Transaction Proximity", which measures the distance between wallets in the transaction graph, and "Easily Attainable Identities (EAIs)", wallets with direct transaction connections to centralized exchanges. Recognizing the limitations of traditional approaches like blocklisting (reactive, slow) and strict allow listing (privacy-invasive, adoption barriers), we propose a system that analyzes transaction patterns to identify wallets with close connections to centralized exchanges. Our directed graph analysis of the Ethereum blockchain reveals that 56% of large USDC wallets (with a lifetime maximum balance greater than $10,000) are EAI and 88% are within one transaction hop of an EAI. For transactions exceeding $2,000, 91% involve at least one EAI. Crucially,…
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