异构跨链交易追踪：面向Solana桥的候选集选择性决策方法
Heterogeneous Cross-Chain Transaction Tracing for Solana Bridges via Candidate-Set Selective Decision
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中文总结 AI 辅助
针对Solana跨链桥交易追踪的语义鸿沟问题，提出候选集选择性决策方法SolTracer，统一事件空间并选择性关联交易，在开放世界场景下F1提升20.16%。
中文摘要 AI 辅助
Solana是一个快速发展的、高吞吐量的区块链平台，吸引了大量流动性和用户活动。然而，这种扩张也引起了非法行为者的注意，他们经常利用跨链桥将非法资金路由到Solana上，以混淆交易谱系。与兼容EVM的平台不同，Solana具有独特的执行动态，且缺乏标准的事件日志，这造成了严重的语义鸿沟，使得现有的追踪方法无法可靠地关联跨账本交易。在本文中，我们形式化了四种面向Solana的跨链交易模式，并提出了一种基于候选集选择性决策的追踪方法，称为SolTracer。SolTracer将不同的执行语义映射到统一的事件空间，并采用候选集选择性决策来可靠地关联目标交易，同时在缺少有效目标时弃权（不执行）。大量实验表明，SolTracer在三个代表性场景中优于最先进（SOTA）方法：封闭世界关联、开放世界关联和跨源链泛化。特别是，在具有50% TA比率的具有挑战性的开放世界设置下，SolTracer相比最强的SOTA基线将F1分数提高了20.16%。利用SolTracer，我们对真实世界的跨链转账进行了实证分析，以研究生态系统动态。我们的分析探讨了桥接机制之间显著的数量-价值差异、跨资产转移的普遍性，以及链上结算与浏览器可见性之间的脱节。
英文摘要
Solana is a rapidly growing high-throughput blockchain platform that has attracted substantial liquidity and user activity. However, this expansion has also drawn the attention of illicit actors, who frequently leverage cross-chain bridges to route illicit funds onto Solana to obfuscate transaction lineage. Unlike EVM-compatible platforms, Solana features distinct execution dynamics and lacks standard event logs, creating severe semantic gaps that prevent existing tracing methods from reliably correlating cross-ledger transactions. In this paper, we formalize four types of Solana-bound cross-chain transaction modes and propose a candidate-set selective decision-based tracing method called SolTracer. SolTracer maps disparate execution semantics into a unified event space and employs candidate-set selective decision-making to reliably associate target transactions while abstaining when valid targets are absent. Extensive experiments demonstrate that SolTracer outperforms state-of-the-art (SOTA) methods across three representative scenarios: closed-world association, open-world association, and cross-source-chain generalization. In particular, under the challenging open-world setting with a 50% TA ratio, SolTracer improves the F1 score by 20.16% over the strongest SOTA baseline. Utilizing SolTracer, we conduct an empirical analysis on real-world cross-chain transfers to investigate ecosystem dynamics. Our analysis explores the stark count-value divergence across bridge mechanisms, the prevalence of cross-asset shifts, and the decoupling between on-chain settlement and explorer visibility.
发表机构
- North University of China（中北大学）
- Beijing Institute of Technology（北京理工大学）
机构由 AI 辅助整理，请以论文原文为准。
