arXiv:2507.19411cs.LGcs.CR2025-07

通过动态分析流动性提供者影响,精准识别高风险鲸鱼,提升去中心化交易协议安全

SILS: Strategic Influence on Liquidity Stability and Whale Detection in Concentrated-Liquidity DEXs

  • 基于链上事件与智能合约追踪,构建时间加权流动性指标
  • 提出LSIS评分,量化单个提供者退出对市场稳定的影响
  • 可发现传统方法遗漏的高危大户,适合DeFi风控与交易信号场景

传统方法依赖名义资本规模或表面活跃度来识别集中流动性做市商(CLMM)中的关键流动性提供者(LP),常导致风险评估失准。SILS框架采用更精细的方法,将LP视为动态系统性参与者,其行为直接影响市场稳定性,实现从静态体积分析到动态影响评估的根本转变。该框架利用链上事件日志与智能合约执行轨迹,计算指数时间加权流动性(ETWL)分布,并应用无监督异常检测。核心创新在于引入流动性稳定性影响得分(LSIS),一种反事实指标,衡量若某LP撤资将导致市场的潜在恶化程度。该组合方法提供更全面、真实的LP影响刻画,超越现有方法的二元分类陷阱。SILS能准确识别高影响力LP,包括传统方法遗漏者,支持保护性预言机层与可操作的交易信号,显著增强DeFi生态安全性。该框架带来前所未有的流动性结构透明度与风险洞察,有效减少误报,揭示关键漏报,为协议提供主动风险管理机制,变革DeFi应对非对称流动性行为的能力。

原文摘要 · Abstract (English)

Traditional methods for identifying impactful liquidity providers (LPs) in Concentrated Liquidity Market Makers (CLMMs) rely on broad measures, such as nominal capital size or surface-level activity, which often lead to inaccurate risk analysis. The SILS framework offers a significantly more detailed approach, characterizing LPs not just as capital holders but as dynamic systemic agents whose actions directly impact market stability. This represents a fundamental paradigm shift from the static, volume-based analysis to a dynamic, impact-focused understanding. This advanced approach uses on-chain event logs and smart contract execution traces to compute Exponential Time-Weighted Liquidity (ETWL) profiles and apply unsupervised anomaly detection. Most importantly, it defines an LP's functional importance through the Liquidity Stability Impact Score (LSIS), a counterfactual metric that measures the potential degradation of the market if the LP withdraws. This combined approach provides a more detailed and realistic characterization of an LP's impact, moving beyond the binary and often misleading classifications used by existing methods. This impact-focused and comprehensive approach enables SILS to accurately identify high-impact LPs-including those missed by traditional methods and supports essential applications like a protective oracle layer and actionable trader signals, thereby significantly enhancing DeFi ecosystem. The framework provides unprecedented transparency into the underlying liquidity structure and associated risks, effectively reducing the common false positives and uncovering critical false negatives found in traditional models. Therefore, SILS provides an effective mechanism for proactive risk management, transforming how DeFi protocols safeguard their ecosystems against asymmetric liquidity behavior.

DeFi安全流动性分析鲸鱼检测

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。