IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100308

Muhammad Hanif , Ehsan Ullah Munir , Muhammad Maaz Rehan , Saima Gulzar Ahmad , Imtiaz Khan , Rossitza Setchi

Protecting intellectual property (IP) in the digital age presents significant challenges due to rapid technological advancements and industrial growth. Traditional methods of registering and securing IP are becoming increasingly ineffective. To address these challenges, a more robust system is needed to control access, prevent unauthorized use, and safeguard digital rights. Despite efforts to transition from central registries to encrypted systems, vulnerabilities still exist that can compromise IP security. Therefore, a comprehensive solution must ensure legal use, prevent misuse, and enhance overall IP protection. This study introduces a robust framework designed to prioritize IP security and protection while addressing financial considerations. Our tiered Blockchain-based approach features logically segregated layers governed by smart contracts, which control access based on predefined agreements set by the IP owner. A common application interface (CAI) via smart contracts simplifies common operation with regard to an IP. The decentralized nature of Blockchain technology ensures unassailable trust, availability, and security. Additionally, we employ a flexible off-chain identity verification and storage mechanism for quick access and improved processing capabilities. Financial aspects tied to digital rights are managed through Blockchain's oracle services, ensuring seamless integration and management. Our integrated solution provides a reliable platform for IP protection, validated through thorough performance evaluations across diverse real-world scenarios. This framework demonstrates significant improvements in efficiency, security, and cost-effectiveness compared to traditional IP protection methods. By leveraging Blockchain's immutable ledger and decentralized network, we enhance the traceability and accountability of IP transactions, reinforcing legal compliance and reducing disputes. Ultimately, this approach ensures that IP is safeguarded, valued, and shared in a manner that benefits creators, consumers, and society as a whole. The rigorous analysis showed significant enhancements in process optimization, technology adoption, efficiency, and cost reduction compared to traditional IP rights protection practices.

由于技术的快速进步和工业的快速增长，在数字时代保护知识产权（IP）提出了重大挑战。注册和保护知识产权的传统方法正变得越来越无效。为了应对这些挑战，需要一个更强大的系统来控制访问、防止未经授权的使用和保护数字权利。尽管努力从中央注册中心过渡到加密系统，但仍然存在可能危及IP安全性的漏洞。因此，全面的解决方案必须确保合法使用，防止滥用，并全面加强知识产权保护。本研究介绍了一个强大的框架，旨在优先考虑知识产权安全和保护，同时解决财务方面的考虑。我们基于区块链的分层方法具有由智能合约管理的逻辑隔离层，智能合约根据IP所有者设置的预定义协议控制访问。通过智能合约的通用应用程序接口（CAI）简化了与IP相关的通用操作。区块链技术的分散性确保了无懈可击的信任、可用性和安全性。此外，我们采用灵活的链下身份验证和存储机制，以实现快速访问和改进的处理能力。与数字版权相关的财务方面通过区块链的oracle服务进行管理，确保无缝集成和管理。我们的集成解决方案为知识产权保护提供了一个可靠的平台，并通过各种实际场景的全面性能评估进行了验证。与传统的知识产权保护方法相比，该框架在效率、安全性和成本效益方面有了显著提高。通过利用区块链的不可变账本和去中心化网络，我们增强了知识产权交易的可追溯性和问责性，加强了法律合规性，减少了争议。最终，这种方法确保知识产权得到保护、重视和共享，使创作者、消费者和整个社会受益。严格的分析表明，与传统的知识产权保护实践相比，在流程优化、技术采用、效率和成本降低方面有了显著提高。

{"title":"Tiered blockchain framework: A secure, trustworthy, and cost-efficient solution for the digital rights protection","authors":"Muhammad Hanif , Ehsan Ullah Munir , Muhammad Maaz Rehan , Saima Gulzar Ahmad , Imtiaz Khan , Rossitza Setchi","doi":"10.1016/j.bcra.2025.100308","DOIUrl":"10.1016/j.bcra.2025.100308","url":null,"abstract":"<div><div>Protecting intellectual property (IP) in the digital age presents significant challenges due to rapid technological advancements and industrial growth. Traditional methods of registering and securing IP are becoming increasingly ineffective. To address these challenges, a more robust system is needed to control access, prevent unauthorized use, and safeguard digital rights. Despite efforts to transition from central registries to encrypted systems, vulnerabilities still exist that can compromise IP security. Therefore, a comprehensive solution must ensure legal use, prevent misuse, and enhance overall IP protection. This study introduces a robust framework designed to prioritize IP security and protection while addressing financial considerations. Our tiered Blockchain-based approach features logically segregated layers governed by smart contracts, which control access based on predefined agreements set by the IP owner. A common application interface (CAI) via smart contracts simplifies common operation with regard to an IP. The decentralized nature of Blockchain technology ensures unassailable trust, availability, and security. Additionally, we employ a flexible off-chain identity verification and storage mechanism for quick access and improved processing capabilities. Financial aspects tied to digital rights are managed through Blockchain's oracle services, ensuring seamless integration and management. Our integrated solution provides a reliable platform for IP protection, validated through thorough performance evaluations across diverse real-world scenarios. This framework demonstrates significant improvements in efficiency, security, and cost-effectiveness compared to traditional IP protection methods. By leveraging Blockchain's immutable ledger and decentralized network, we enhance the traceability and accountability of IP transactions, reinforcing legal compliance and reducing disputes. Ultimately, this approach ensures that IP is safeguarded, valued, and shared in a manner that benefits creators, consumers, and society as a whole. The rigorous analysis showed significant enhancements in process optimization, technology adoption, efficiency, and cost reduction compared to traditional IP rights protection practices.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100308"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing blockchain consensus mechanisms: A comprehensive survey on machine learning applications and optimizations 增强区块链共识机制：机器学习应用和优化的综合调查

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100302

Syamsul Rizal , Dong-Seong Kim

This research examines the incorporation of artificial intelligence (AI) in blockchain consensus algorithms, presenting an extensive overview of current improvements and anticipated effects. We conduct a thorough examination of a diverse array of academic sources, encompassing AI methodologies such as machine learning (ML) techniques—including deep learning and reinforcement learning—applied to blockchain consensus mechanisms. The study highlights critical areas where AI can bolster blockchain performance, including enhancing effectiveness, dependability, and flexibility. Despite the promising benefits that AI integration offers, it also presents complexities and potential security risks, including data centralization and increased computational power requirements. In this analysis, we review the risks and examine the proposed mitigation strategies from existing studies, such as federated learning to preserve data privacy, secure multi-party computation (SMPC) to protect sensitive data, and decentralized AI marketplaces to distribute AI resources fairly. This study makes a significant contribution to the field by emphasizing the dual potential of AI to both improve and challenge blockchain systems. By advocating for balanced approaches that prioritize decentralization and security, our findings aim to provide direction for future research and practical applications in this multidisciplinary field.

本研究探讨了人工智能（AI）在区块链共识算法中的结合，对当前的改进和预期效果进行了广泛的概述。我们对各种学术来源进行了彻底的检查，包括应用于区块链共识机制的机器学习（ML）技术（包括深度学习和强化学习）等人工智能方法。该研究强调了人工智能可以增强bb0性能的关键领域，包括提高效率、可靠性和灵活性。尽管人工智能集成提供了有希望的好处，但它也带来了复杂性和潜在的安全风险，包括数据集中化和计算能力需求的增加。在本分析中，我们回顾了这些风险，并研究了现有研究中提出的缓解策略，例如保护数据隐私的联邦学习、保护敏感数据的安全多方计算（SMPC），以及公平分配人工智能资源的分散人工智能市场。这项研究通过强调人工智能在改进和挑战区块链系统方面的双重潜力，对该领域做出了重大贡献。通过倡导优先考虑去中心化和安全性的平衡方法，我们的研究结果旨在为这一多学科领域的未来研究和实际应用提供方向。

{"title":"Enhancing blockchain consensus mechanisms: A comprehensive survey on machine learning applications and optimizations","authors":"Syamsul Rizal , Dong-Seong Kim","doi":"10.1016/j.bcra.2025.100302","DOIUrl":"10.1016/j.bcra.2025.100302","url":null,"abstract":"<div><div>This research examines the incorporation of artificial intelligence (AI) in blockchain consensus algorithms, presenting an extensive overview of current improvements and anticipated effects. We conduct a thorough examination of a diverse array of academic sources, encompassing AI methodologies such as machine learning (ML) techniques—including deep learning and reinforcement learning—applied to blockchain consensus mechanisms. The study highlights critical areas where AI can bolster blockchain performance, including enhancing effectiveness, dependability, and flexibility. Despite the promising benefits that AI integration offers, it also presents complexities and potential security risks, including data centralization and increased computational power requirements. In this analysis, we review the risks and examine the proposed mitigation strategies from existing studies, such as federated learning to preserve data privacy, secure multi-party computation (SMPC) to protect sensitive data, and decentralized AI marketplaces to distribute AI resources fairly. This study makes a significant contribution to the field by emphasizing the dual potential of AI to both improve and challenge blockchain systems. By advocating for balanced approaches that prioritize decentralization and security, our findings aim to provide direction for future research and practical applications in this multidisciplinary field.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100302"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TrustChain: a privacy protection smart contract model with trusted execution environment TrustChain：一个具有可信执行环境的隐私保护智能合约模型

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100296

Fengyu Wu , Ayong Ye , Yiqing Diao , Yuexin Zhang , Jianwei Chen , Chuan Huang

With the booming development of blockchain, it has gradually gained wide attention in the Internet of Things (IoT), finance, and other fields. However, due to the shared nature of blockchain ledgers among multiple users, sensitive user information, such as transaction amounts and private agreements, can be easily exposed. This poses significant privacy concerns for blockchain users. To address this issue, we propose TrustChain, a high-performance smart contract model based on the Trusted Execution Environment (TEE). TrustChain aims to safeguard the privacy of smart contract codes and user data by leveraging the secure execution environment provided by the TEE. Specifically, we introduce the TEE to run the smart contract with security and privacy without introducing a heavyweight cryptographic algorithm, thus improving the performance of the system. When running smart contracts, the operate nodes equipped with TEE ensure that the Operating System (OS) of the node itself cannot access the data within the TEE. This isolation effectively separates the sensitive information of the smart contract from the external environment. Furthermore, we introduce Verifiable Random Functions (VRFs) to randomly choose the operate nodes to prevent collusion attacks, further improving the security of the model. The graph ledger, based on the Directed Acyclic Graph (DAG), is used to adapt to the high-performance characteristics of a smart contract system based on the TEE. Finally, we simulate the scheme in TrustZone and demonstrate the feasibility of TrustChain through a series of experiments and analyses. The analysis and experimental results demonstrate that our solution exhibits excellent privacy protection performance and achieves higher throughput compared to traditional smart contracts.

随着b区块链的蓬勃发展，b区块链在物联网、金融等领域逐渐受到广泛关注。然而，由于区块链分类账在多个用户之间的共享特性，敏感的用户信息（如交易金额和私人协议）很容易暴露。这给b区块链用户带来了严重的隐私问题。为了解决这个问题，我们提出了基于可信执行环境（TEE）的高性能智能合约模型TrustChain。TrustChain旨在利用TEE提供的安全执行环境来保护智能合约代码和用户数据的隐私。具体来说，我们在不引入重量级加密算法的情况下引入TEE来运行具有安全性和隐私性的智能合约，从而提高了系统的性能。在运行智能合约时，配备TEE的操作节点确保节点本身的操作系统（OS）无法访问TEE内的数据。这种隔离有效地将智能合约的敏感信息与外部环境隔离开来。此外，我们引入可验证随机函数（vrf）来随机选择操作节点，以防止共谋攻击，进一步提高了模型的安全性。基于有向无环图（DAG）的图形分类帐用于适应基于TEE的智能合约系统的高性能特性。最后，我们在TrustZone中对该方案进行了仿真，并通过一系列的实验和分析证明了TrustChain的可行性。分析和实验结果表明，与传统智能合约相比，我们的解决方案具有出色的隐私保护性能，并且实现了更高的吞吐量。

{"title":"TrustChain: a privacy protection smart contract model with trusted execution environment","authors":"Fengyu Wu , Ayong Ye , Yiqing Diao , Yuexin Zhang , Jianwei Chen , Chuan Huang","doi":"10.1016/j.bcra.2025.100296","DOIUrl":"10.1016/j.bcra.2025.100296","url":null,"abstract":"<div><div>With the booming development of blockchain, it has gradually gained wide attention in the Internet of Things (IoT), finance, and other fields. However, due to the shared nature of blockchain ledgers among multiple users, sensitive user information, such as transaction amounts and private agreements, can be easily exposed. This poses significant privacy concerns for blockchain users. To address this issue, we propose TrustChain, a high-performance smart contract model based on the Trusted Execution Environment (TEE). TrustChain aims to safeguard the privacy of smart contract codes and user data by leveraging the secure execution environment provided by the TEE. Specifically, we introduce the TEE to run the smart contract with security and privacy without introducing a heavyweight cryptographic algorithm, thus improving the performance of the system. When running smart contracts, the operate nodes equipped with TEE ensure that the Operating System (OS) of the node itself cannot access the data within the TEE. This isolation effectively separates the sensitive information of the smart contract from the external environment. Furthermore, we introduce Verifiable Random Functions (VRFs) to randomly choose the operate nodes to prevent collusion attacks, further improving the security of the model. The graph ledger, based on the Directed Acyclic Graph (DAG), is used to adapt to the high-performance characteristics of a smart contract system based on the TEE. Finally, we simulate the scheme in TrustZone and demonstrate the feasibility of TrustChain through a series of experiments and analyses. The analysis and experimental results demonstrate that our solution exhibits excellent privacy protection performance and achieves higher throughput compared to traditional smart contracts.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100296"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DBESN: A novel model for detecting and identifying malicious code in a smart contract DBESN：一种用于检测和识别智能合约中恶意代码的新模型

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100304

Punam Bedi , Vinita Jindal , Ningyao Ningshen , Pushkar Gole

Smart contracts represent a predefined set of rules invoked when specific conditions are met within blockchain networks, eliminating the need for a centralized authority to validate the transactions. The absence of a central authority can potentially expose smart contracts to fraudulent behavior. Moreover, implementation flaws in smart contracts can be exploited to cause unintended behavior, resulting in security or financial risks. Traditionally, the identification of vulnerabilities in smart contracts has relied on methods such as pattern matching, data flow analysis, and input testing. While these techniques are foundational, they are constrained by human limitations and may not comprehensively address the full spectrum of potential issues. This necessitates more advanced approaches to ensure robust security and reliability. Therefore, in the literature, numerous researchers have leveraged different machine learning (ML) and deep learning (DL) techniques to classify normal and malicious smart contracts. However, the existing literature either grapples with class imbalance issues or relies on conventional methods. Moreover, the existing research often falls short of locating the exact location of malicious code within the smart contracts. Therefore, to address these gaps, this paper proposes a novel model called the dual-branch encoder Siamese network (DBESN) for detecting malicious smart contracts. Furthermore, this model is extended to precisely identify the region of the vulnerable code fragment within the smart contract using the local interpretable model-agnostic explanations (LIME) algorithm. Experimental results demonstrated a performance accuracy of 98.62% and an F1-score of 99.30% with an inference time of 0.296 s. Given the high performance coupled with the low inference time of the proposed DBESN model, it is suitable for deployment within blockchain networks to detect and identify malicious smart contracts effectively and efficiently.

智能合约代表了区块链网络中满足特定条件时调用的一组预定义规则，从而消除了对中心化机构验证交易的需要。缺乏中央权威可能会使智能合约暴露于欺诈行为。此外，智能合约中的实施缺陷可能会被利用来引发意外行为，从而导致安全或财务风险。传统上，智能合约中的漏洞识别依赖于模式匹配、数据流分析和输入测试等方法。虽然这些技术是基础的，但它们受到人类局限性的限制，可能无法全面解决所有潜在问题。这就需要更先进的方法来确保强大的安全性和可靠性。因此，在文献中，许多研究人员利用不同的机器学习（ML）和深度学习（DL）技术对正常和恶意智能合约进行分类。然而，现有的文献要么与阶级不平衡问题作斗争，要么依赖于传统的方法。此外，现有的研究往往无法确定恶意代码在智能合约中的确切位置。因此，为了解决这些差距，本文提出了一种称为双分支编码器暹罗网络（DBESN）的新模型，用于检测恶意智能合约。此外，该模型被扩展到使用本地可解释模型不可知解释（LIME）算法精确识别智能合约中易受攻击的代码片段的区域。实验结果表明，该算法的性能准确率为98.62%，f1得分为99.30%，推理时间为0.296 s。鉴于所提出的DBESN模型的高性能和低推理时间，它适合部署在区块链网络中，有效地检测和识别恶意智能合约。

{"title":"DBESN: A novel model for detecting and identifying malicious code in a smart contract","authors":"Punam Bedi , Vinita Jindal , Ningyao Ningshen , Pushkar Gole","doi":"10.1016/j.bcra.2025.100304","DOIUrl":"10.1016/j.bcra.2025.100304","url":null,"abstract":"<div><div>Smart contracts represent a predefined set of rules invoked when specific conditions are met within blockchain networks, eliminating the need for a centralized authority to validate the transactions. The absence of a central authority can potentially expose smart contracts to fraudulent behavior. Moreover, implementation flaws in smart contracts can be exploited to cause unintended behavior, resulting in security or financial risks. Traditionally, the identification of vulnerabilities in smart contracts has relied on methods such as pattern matching, data flow analysis, and input testing. While these techniques are foundational, they are constrained by human limitations and may not comprehensively address the full spectrum of potential issues. This necessitates more advanced approaches to ensure robust security and reliability. Therefore, in the literature, numerous researchers have leveraged different machine learning (ML) and deep learning (DL) techniques to classify normal and malicious smart contracts. However, the existing literature either grapples with class imbalance issues or relies on conventional methods. Moreover, the existing research often falls short of locating the exact location of malicious code within the smart contracts. Therefore, to address these gaps, this paper proposes a novel model called the dual-branch encoder Siamese network (DBESN) for detecting malicious smart contracts. Furthermore, this model is extended to precisely identify the region of the vulnerable code fragment within the smart contract using the local interpretable model-agnostic explanations (LIME) algorithm. Experimental results demonstrated a performance accuracy of 98.62% and an F1-score of 99.30% with an inference time of 0.296 s. Given the high performance coupled with the low inference time of the proposed DBESN model, it is suitable for deployment within blockchain networks to detect and identify malicious smart contracts effectively and efficiently.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100304"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

WHO revises global framework for monitoring nonpharmaceutical interventions in health emergencies 世卫组织修订突发卫生事件非药物干预措施监测全球框架

Q1 Social Sciences

Journal of Biosafety and Biosecurity

Pub Date : 2025-12-01 DOI: 10.1016/j.jobb.2025.12.001

引用次数: 0

E-Guard: a vulnerability detection tool for smart contracts in electric power systems E-Guard：电力系统智能合约漏洞检测工具

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100309

Feng Du, Junwei Ma, Liang Gu, Honglin Xue, Xiaowei Hao, Xin Gong, Rongsheng Li

The application of smart contracts in electric power systems is widespread. However, vulnerabilities in smart contracts can cause significant economic losses and require careful attention. Smart contracts in electric power systems have domain-specific characteristics that differ from traditional public blockchain applications. As a result, existing vulnerability detection tools cannot be directly applied to these systems. To address this challenge, we design a vulnerability detection tool called E-Guard specifically for smart contracts in electric power systems. E-Guard uses a tailored intermediate representation (IR) known as EIR, which provides control flow and data flow information more suited to the business logic of electric power systems than traditional static analysis tools.

We identify and summarize three types of vulnerabilities unique to electric power systems based on expert knowledge. Experimental results show that E-Guard significantly outperforms traditional static analysis tools in detecting these three types of vulnerabilities. Additionally, the extra overhead generated by using EIR is minimal and negligible. This demonstrates that E-Guard is an effective and efficient tool for enhancing the security of smart contracts in electric power systems.

智能合约在电力系统中的应用非常广泛。然而，智能合约中的漏洞可能会造成重大的经济损失，需要谨慎关注。电力系统中的智能合约具有与传统公共bb0应用不同的领域特定特征。因此，现有的漏洞检测工具无法直接应用于这些系统。为了应对这一挑战，我们设计了一个名为E-Guard的漏洞检测工具，专门用于电力系统中的智能合约。E-Guard使用定制的中间表示（IR），称为EIR，它提供比传统静态分析工具更适合电力系统业务逻辑的控制流和数据流信息。基于专家知识，我们识别并总结了电力系统特有的三种类型的漏洞。实验结果表明，E-Guard在检测这三种漏洞方面明显优于传统的静态分析工具。此外，使用EIR产生的额外开销很小，可以忽略不计。这表明E-Guard是提高电力系统智能合约安全性的有效工具。

{"title":"E-Guard: a vulnerability detection tool for smart contracts in electric power systems","authors":"Feng Du, Junwei Ma, Liang Gu, Honglin Xue, Xiaowei Hao, Xin Gong, Rongsheng Li","doi":"10.1016/j.bcra.2025.100309","DOIUrl":"10.1016/j.bcra.2025.100309","url":null,"abstract":"<div><div>The application of smart contracts in electric power systems is widespread. However, vulnerabilities in smart contracts can cause significant economic losses and require careful attention. Smart contracts in electric power systems have domain-specific characteristics that differ from traditional public blockchain applications. As a result, existing vulnerability detection tools cannot be directly applied to these systems. To address this challenge, we design a vulnerability detection tool called E-Guard specifically for smart contracts in electric power systems. E-Guard uses a tailored intermediate representation (IR) known as EIR, which provides control flow and data flow information more suited to the business logic of electric power systems than traditional static analysis tools.</div><div>We identify and summarize three types of vulnerabilities unique to electric power systems based on expert knowledge. Experimental results show that E-Guard significantly outperforms traditional static analysis tools in detecting these three types of vulnerabilities. Additionally, the extra overhead generated by using EIR is minimal and negligible. This demonstrates that E-Guard is an effective and efficient tool for enhancing the security of smart contracts in electric power systems.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100309"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145790095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A noncooperative game theory-based incentive model for scaling permissioned blockchain networks 基于非合作博弈论的区块链网络扩容激励模型

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100298

Richard Lapin, Somnath Mazumdar

Blockchain offers decentralization and data security in a trustless environment. Transaction details are logged to trace a transaction trail. Blockchain has multiple components that are crucial to overall performance. One such component is the consensus model. It is responsible for network scaling, and blockchain suffers from scaling problems. It is also important for the growth and existence of the network to satisfy the transaction proposers and validators. To maintain the network, incentives are given to validators in a digital asset form, commonly using cryptocurrency. A lack of appropriate incentives can lead to suboptimal network performance, preventing networks from reaching their full potential. This paper introduces a noncooperative game theory-based incentive model to improve network performance while enhancing the scaling feature of a permissioned blockchain network. The model is generic and focuses on the incentive structure of the network. The proposed model is based on five design goals. They are generability, scalability, energy awareness, fairness, and dynamism. The proposed model is not a consensus model but a complement to a suitable voting-based consensus model. An extensive simulation campaign was conducted to demonstrate the effectiveness of the proposed model.

区块链在不可信的环境中提供去中心化和数据安全性。记录事务详细信息以跟踪事务轨迹。区块链有多个对整体性能至关重要的组件。其中一个组成部分是共识模型。它负责网络扩展，而区块链存在扩展问题。满足交易提议者和验证者对网络的发展和存在也很重要。为了维护网络，以数字资产形式向验证者提供激励，通常使用加密货币。缺乏适当的激励可能导致网络性能不理想，从而阻止网络充分发挥其潜力。本文提出了一种基于非合作博弈论的激励模型，以提高网络性能，同时增强许可区块链网络的扩展特性。该模型具有通用性，关注网络的激励结构。提出的模型基于五个设计目标。它们是可扩展性、可扩展性、能源意识、公平性和动态性。提出的模型不是共识模型，而是对合适的基于投票的共识模型的补充。进行了广泛的仿真活动来证明所提出模型的有效性。

{"title":"A noncooperative game theory-based incentive model for scaling permissioned blockchain networks","authors":"Richard Lapin, Somnath Mazumdar","doi":"10.1016/j.bcra.2025.100298","DOIUrl":"10.1016/j.bcra.2025.100298","url":null,"abstract":"<div><div>Blockchain offers decentralization and data security in a trustless environment. Transaction details are logged to trace a transaction trail. Blockchain has multiple components that are crucial to overall performance. One such component is the consensus model. It is responsible for network scaling, and blockchain suffers from scaling problems. It is also important for the growth and existence of the network to satisfy the transaction proposers and validators. To maintain the network, incentives are given to validators in a digital asset form, commonly using cryptocurrency. A lack of appropriate incentives can lead to suboptimal network performance, preventing networks from reaching their full potential. This paper introduces a noncooperative game theory-based incentive model to improve network performance while enhancing the scaling feature of a permissioned blockchain network. The model is generic and focuses on the incentive structure of the network. The proposed model is based on five design goals. They are generability, scalability, energy awareness, fairness, and dynamism. The proposed model is not a consensus model but a complement to a suitable voting-based consensus model. An extensive simulation campaign was conducted to demonstrate the effectiveness of the proposed model.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100298"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analyzing the impact of elusive faults on blockchain reliability 分析难以捉摸的故障对区块链可靠性的影响

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100295

Fernando Richter Vidal, Naghmeh Ivaki, Nuno Laranjeiro

Blockchain has recently become very popular due to its use in cryptocurrencies and potential application in various domains (e.g., retail, healthcare, and insurance). The smart contract is a key part of blockchain systems and specifies an agreement between transaction participants. Nowadays, smart contracts are being deployed to carry residual faults, including severe vulnerabilities that lead to different types of failures at runtime. Fault detection tools can be used to detect faults that may then be removed from the code before deployment. However, in the case of smart contracts, the common opinion is that tools are immature and ineffective. In this work, we carry out a fault injection campaign to empirically analyze the runtime impact that realistic faults present in smart contracts may have on the reliability of blockchain systems. We pay particular attention to the faults that elude popular smart contract verification tools and show if and in which ways the faults lead the blockchain system to fail at runtime. We map the observations to the fault detection capabilities of three state-of-the-art fault detection tools, namely Mythril, Slither, and Securify. The results show that the tools individually have poor detection capabilities (e.g., Securify with 6.4% accuracy and Mythril with 60% accuracy) or tend to generate false alerts (i.e., only 1.74% of Slither's alerts are correct). The results also show several elusive faults responsible for severe blockchain failures, such as A_MCV, which impacts the integrity of the ledger, and I_MVMSV, which causes gas depletion, just to name a few.

区块链最近因其在加密货币中的使用以及在各个领域（例如零售、医疗保健和保险）的潜在应用而变得非常受欢迎。智能合约是区块链系统的关键部分，它指定了交易参与者之间的协议。如今，智能合约被部署为携带残余故障，包括在运行时导致不同类型故障的严重漏洞。故障检测工具可用于检测可能在部署前从代码中删除的错误。然而，就智能合约而言，普遍的观点是工具不成熟且无效。在这项工作中，我们开展了一个故障注入活动，以经验分析智能合约中存在的实际故障可能对区块链系统的可靠性产生的运行时影响。我们特别关注流行的智能合约验证工具无法识别的错误，并显示这些错误是否以及以何种方式导致区块链系统在运行时失败。我们将观察结果映射到三个最先进的故障检测工具的故障检测功能，即Mythril， Slither和Securify。结果表明，这些工具各自的检测能力都很差（例如，Securify的准确率为6.4%，Mythril的准确率为60%），或者倾向于生成错误警报（即，Slither的警报中只有1.74%是正确的）。结果还显示了导致区块链严重故障的几个难以捉摸的故障，例如影响分类账完整性的A_MCV和导致天然气枯竭的I_MVMSV，仅举几例。

{"title":"Analyzing the impact of elusive faults on blockchain reliability","authors":"Fernando Richter Vidal, Naghmeh Ivaki, Nuno Laranjeiro","doi":"10.1016/j.bcra.2025.100295","DOIUrl":"10.1016/j.bcra.2025.100295","url":null,"abstract":"<div><div>Blockchain has recently become very popular due to its use in cryptocurrencies and potential application in various domains (e.g., retail, healthcare, and insurance). The smart contract is a key part of blockchain systems and specifies an agreement between transaction participants. Nowadays, smart contracts are being deployed to carry residual faults, including severe vulnerabilities that lead to different types of failures at runtime. Fault detection tools can be used to detect faults that may then be removed from the code before deployment. However, in the case of smart contracts, the common opinion is that tools are immature and ineffective. In this work, we carry out a fault injection campaign to empirically analyze the runtime impact that realistic faults present in smart contracts may have on the reliability of blockchain systems. We pay particular attention to the faults that elude popular smart contract verification tools and show if and in which ways the faults lead the blockchain system to fail at runtime. We map the observations to the fault detection capabilities of three state-of-the-art fault detection tools, namely Mythril, Slither, and Securify. The results show that the tools individually have poor detection capabilities (e.g., Securify with 6.4% accuracy and Mythril with 60% accuracy) or tend to generate false alerts (i.e., only 1.74% of Slither's alerts are correct). The results also show several elusive faults responsible for severe blockchain failures, such as A_MCV, which impacts the integrity of the ledger, and I_MVMSV, which causes gas depletion, just to name a few.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100295"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Redactable blockchains with integer-valued polynomials 具有整数值多项式的可读区块链

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100297

Udomsak Rakwongwan , Phiraphat Sutthimat , Rattiya Meesa

Blockchain technology has rapidly ascended as a pivotal innovation in the financial sector, renowned for its robust tamper-resistant properties inherent in hash-based systems. Despite its strengths, the blockchain's rigidity poses significant challenges in the timely rectification of fraudulent transactions, as initiating a fork to correct the ledger is both resource-intensive and time-consuming. Such delays in addressing fraud can have detrimental effects on the broader economic landscape. Addressing this critical issue, this study introduces a novel polynomial-based blockchain architecture that uses integer-valued polynomials (IVPs) for data organization within each block. This novel structure allows for the modification of data while preserving the chronological integrity of the blockchain. IVPs provide a methodical framework that not only facilitates the necessary alterations but also implements nuanced control over the complexity of these modifications. Significantly, this approach demonstrates a substantial reduction in time consumption for data modifications compared to traditional Lagrange polynomial methods, enhancing the blockchain's responsiveness in dynamic financial environments. Our empirical analysis confirms the efficiency and practicality of the proposed blockchain model. Furthermore, a comprehensive theoretical examination coupled with practical assessments reveals that this adaptable blockchain framework, when integrated with advanced cryptographic and privacy-preserving methodologies, offers a versatile solution with extensive applicability across various transactional environments.

区块链技术已迅速上升为金融领域的关键创新，以其基于哈希的系统固有的强大抗篡改特性而闻名。尽管区块链有其优势，但它的刚性在及时纠正欺诈性交易方面带来了重大挑战，因为启动一个分叉来纠正分类账既耗费资源又耗时。在解决欺诈问题上的这种拖延可能对更广泛的经济格局产生不利影响。为了解决这一关键问题，本研究引入了一种新的基于多项式的区块链架构，该架构使用整数值多项式（ivp）在每个块内进行数据组织。这种新颖的结构允许对数据进行修改，同时保持区块链的时间顺序完整性。ivp提供了一个有条理的框架，不仅促进了必要的修改，而且实现了对这些修改复杂性的细微控制。值得注意的是，与传统的拉格朗日多项式方法相比，这种方法大大减少了数据修改的时间消耗，增强了区块链在动态金融环境中的响应能力。实证分析证实了区块链模型的有效性和实用性。此外，结合实际评估的全面理论研究表明，当与高级加密和隐私保护方法集成时，这种适应性强的区块链框架提供了一种广泛适用于各种事务环境的通用解决方案。

{"title":"Redactable blockchains with integer-valued polynomials","authors":"Udomsak Rakwongwan , Phiraphat Sutthimat , Rattiya Meesa","doi":"10.1016/j.bcra.2025.100297","DOIUrl":"10.1016/j.bcra.2025.100297","url":null,"abstract":"<div><div>Blockchain technology has rapidly ascended as a pivotal innovation in the financial sector, renowned for its robust tamper-resistant properties inherent in hash-based systems. Despite its strengths, the blockchain's rigidity poses significant challenges in the timely rectification of fraudulent transactions, as initiating a fork to correct the ledger is both resource-intensive and time-consuming. Such delays in addressing fraud can have detrimental effects on the broader economic landscape. Addressing this critical issue, this study introduces a novel polynomial-based blockchain architecture that uses integer-valued polynomials (IVPs) for data organization within each block. This novel structure allows for the modification of data while preserving the chronological integrity of the blockchain. IVPs provide a methodical framework that not only facilitates the necessary alterations but also implements nuanced control over the complexity of these modifications. Significantly, this approach demonstrates a substantial reduction in time consumption for data modifications compared to traditional Lagrange polynomial methods, enhancing the blockchain's responsiveness in dynamic financial environments. Our empirical analysis confirms the efficiency and practicality of the proposed blockchain model. Furthermore, a comprehensive theoretical examination coupled with practical assessments reveals that this adaptable blockchain framework, when integrated with advanced cryptographic and privacy-preserving methodologies, offers a versatile solution with extensive applicability across various transactional environments.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100297"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart contract classification based on neural clustering and semantic feature enhancement 基于神经聚类和语义特征增强的智能合约分类

IF 5.6 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

Blockchain-Research and Applications

Pub Date : 2025-12-01 DOI: 10.1016/j.bcra.2025.100303

Gang Tian , Pengxiang Wang , Rui Wang , Yidong Du

Smart contract classification holds significant application value in the field of blockchain. However, existing methods suffer from inefficiencies and high computational complexity when dealing with smart contract data. To address these issues, this paper proposes a cluster-BERT model based on neural clustering techniques. The model reduces the computational burden of self-attention mechanisms by clustering attention heads, thereby improving training efficiency. The cluster-BERT model comprises multiple modules. Module 1 preprocesses smart contract data, converting abstract syntax trees and graph structure features into text representations suitable for BERT models. Module 2 serves as the core of the model, introducing neural clustering methods to reduce computational complexity. Module 3 further optimizes the model by finding the optimal number of centroids, achieving a balance between training efficiency and classification accuracy. Experimental results show that our proposed cluster-BERT achieves an accuracy of 91.42%, a recall of 91.44%, and an F1 score of 91.43%, which indicates a noticeable improvement over the baseline model. Our model reduces computational complexity from quadratic to linear, resulting in an average reduction of 8.48% in training time and 7.88% in prediction time compared to the baseline model. On the smart contract dataset, the accuracy and precision of our model outperformed other models proposed in recent years by 1–2 percentage points on average.

智能合约分类在区块链领域具有重要的应用价值。然而，现有方法在处理智能合约数据时存在效率低下和计算复杂性高的问题。为了解决这些问题，本文提出了一种基于神经聚类技术的聚类- bert模型。该模型通过对注意头进行聚类，减少了自注意机制的计算负担，从而提高了训练效率。cluster-BERT模型由多个模块组成。模块1对智能合约数据进行预处理，将抽象语法树和图形结构特征转换为适合BERT模型的文本表示。模块2作为模型的核心，引入神经聚类方法降低计算复杂度。模块3进一步优化模型，找到最优的质心个数，达到训练效率和分类精度之间的平衡。实验结果表明，本文提出的聚类bert的准确率为91.42%，召回率为91.44%，F1分数为91.43%，与基线模型相比有了明显的提高。我们的模型将计算复杂度从二次型降低到线性，与基线模型相比，训练时间平均减少8.48%，预测时间平均减少7.88%。在智能合约数据集上，我们的模型的准确度和精密度比近年来提出的其他模型平均高出1-2个百分点。

{"title":"Smart contract classification based on neural clustering and semantic feature enhancement","authors":"Gang Tian , Pengxiang Wang , Rui Wang , Yidong Du","doi":"10.1016/j.bcra.2025.100303","DOIUrl":"10.1016/j.bcra.2025.100303","url":null,"abstract":"<div><div>Smart contract classification holds significant application value in the field of blockchain. However, existing methods suffer from inefficiencies and high computational complexity when dealing with smart contract data. To address these issues, this paper proposes a cluster-BERT model based on neural clustering techniques. The model reduces the computational burden of self-attention mechanisms by clustering attention heads, thereby improving training efficiency. The cluster-BERT model comprises multiple modules. Module 1 preprocesses smart contract data, converting abstract syntax trees and graph structure features into text representations suitable for BERT models. Module 2 serves as the core of the model, introducing neural clustering methods to reduce computational complexity. Module 3 further optimizes the model by finding the optimal number of centroids, achieving a balance between training efficiency and classification accuracy. Experimental results show that our proposed cluster-BERT achieves an accuracy of 91.42%, a recall of 91.44%, and an F1 score of 91.43%, which indicates a noticeable improvement over the baseline model. Our model reduces computational complexity from quadratic to linear, resulting in an average reduction of 8.48% in training time and 7.88% in prediction time compared to the baseline model. On the smart contract dataset, the accuracy and precision of our model outperformed other models proposed in recent years by 1–2 percentage points on average.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100303"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

信息工程最新文献