面向DeFi中价格操纵攻击的全生命周期检测与防御框架
A Lifecycle-Oriented Detection and Defense Framework for Price Manipulation Attacks in DeFi
- Hainan University（海南大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究针对DeFi价格操纵攻击，基于预言机生命周期构建三层攻击树，结合Fuzzy-AHP与VaR量化风险，开发基于Slither的自动检测工具，提出多层防御策略，有效降低价格偏差且检测性能优于现有工具。
AI中文摘要：
针对去中心化金融（DeFi）中频繁发生的预言机价格操纵攻击，本文研究了攻击模式、漏洞类型、风险评估、自动检测及防御策略。基于预言机生命周期理论，构建了覆盖物理层、协议层和应用层的三层攻击树，以分析攻击链并确定数据选举阶段为关键入侵点。总结出四类主要合约级漏洞：价格数据流验证不足、预言机调用风险、跨合约调用不受控以及AMM价格读取逻辑缺陷。将模糊层次分析法（Fuzzy-AHP）与风险价值（VaR）模型结合，量化风险因子并构建涵盖技术、市场、治理及合约风险的风险矩阵。基于扩展的Slither框架，利用污点跟踪与模式匹配开发了自动检测工具。最后，提出多层防御策略，在数据源层集成可信执行环境，在智能合约层采用TWAP平滑与自适应熔断机制，在操作系统层采用优化的内核网络配置。实验表明，所提方法将攻击引发的价格偏差从55.56%降至5%以下；该检测工具准确率达94.38%，召回率达92.31%，优于现有开源工具。
英文摘要：
Aiming at frequent oracle price manipulation attacks in Decentralized Finance (DeFi), this paper investigates attack patterns, vulnerability types, risk assessment, automated detection, and defense strategies. Based on Oracle lifecycle theory, a three-layer attack tree covering the physical, protocol, and application layers is constructed to analyze the attack chain and identify the data election stage as a key intrusion point. Four major contract-level vulnerabilities are summarized: insufficient validation of price data flow, oracle call risks, uncontrolled cross-contract calls, and defects in AMM price reading logic. Fuzzy-AHP and Value-at-Risk (VaR) models are combined to quantify risk factors and construct a risk matrix covering technology, market, governance, and contract risks. An automated detection tool based on an extended Slither framework is developed using taint tracking and pattern matching. Finally, a multi-layer defense strategy is proposed, integrating trusted execution environments at the data source layer, TWAP smoothing and adaptive circuit breakers at the smart contract layer, and optimized kernel network configurations at the operating system layer. Experiments show that the proposed approach reduces attack-induced price deviation from 55.56% to below 5%. The detection tool achieves 94.38% accuracy and 92.31% recall, outperforming existing open-source tools.
