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arXiv Machine Learning By Seongchan Park, Hyunho Jeon, Byungsoo Kang, Gaeun Kim, Minseob So, Seongyong Kim

On-Chain Behavioral Signatures for Classifying Centralized Exchange Addresses on Ethereum Using Proof-of-Reserves

Read the original on arXiv Machine Learning →

The paper presents a classification framework that uses Proof-of-Reserves disclosures to identify centralized exchange (CEX) addresses on Ethereum. It analyzes 3,033,857 addresses from 15 CEXs and five non-CEX categories, extracting 58 on-chain behavioral features and demonstrating that LightGBM outperforms logistic regression across various lookback windows. Key predictive signals include gas behavior, ERC‑20 token activity, and internal transactions, and the authors release a feature dataset for reproducible research.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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