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    Web 3.0数字经济风险感知技术综述

    Survey of Risk Perception Technology for Web 3.0 Digital Economic

    • 摘要: Web 3.0数字经济体系以区块链平台为基础设施,围绕加密货币、NFT、数字藏品等数字资产和去中心化金融(DeFi)、游戏金融(GameFi)等去中心化应用(DApp)开展各项社会经济活动. 在公有链和开放联盟链下,作为DApp内核的智能合约可以由任何个人或组织予以部署,并对全体用户可见及可调用. 这种开放性给经济发展带来了新的机遇,同时也蕴含了许多金融风险. 以智能合约为中心分析了Web 3.0数字经济潜在的风险,并从智能合约的编码、功能、应用3个层面总结了风险感知技术的研究现状. 首先介绍了智能合约漏洞检测技术的研究挑战、安全漏洞类型和4类漏洞检测方法;其次分析了常见的智能合约骗局类型,并根据训练数据的不同分类总结了现有的智能合约骗局识别技术;接着介绍了基于区块链交易记录对4种非法交易行为进行检测的技术现状;最后结合对现有工作局限性的分析,展望了未来的研究方向.

       

      Abstract: The Web 3.0 digital economic system takes the blockchain platform as its infrastructure, and revolves around the digital assets such as cryptocurrencies, NFTs, digital collectibles, and decentralized applications (DApps) like decentralized finance (DeFi) and gaming finance (GameFi) to conduct various socio-economic activities. Smart contracts are the core of DApps on the public blockchains and the public permissioned blockchains, such as Ethereum, Solana, EOSIO, Findora, Antchain, ChainMaker, et al. They can be deployed by any individual or organization, and are visible and accessible to all blockchain users. This openness brings new opportunities for economic development while also harboring numerous financial risks. This paper analyzes potential risks for Web 3.0 digital economic by focusing on smart contract and summarizes the current research on risk perception technology from three aspects: encoding, functionality, and application of smart contracts. The paper first introduces the research challenges, security vulnerability types, and four categories of vulnerability detection methods in smart contract vulnerability detection technology. Next, it analyzes common types of smart contract scams and summarizes existing scam recognition techniques based on different classifications of training data. Subsequently, it introduces the current state of technology for detecting four types of illicit transactions behaviors based on blockchain transaction records. Lastly, by analyzing the limitations of existing work, it envisions the future research directions.

       

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