Pub Date : 2026-02-01DOI: 10.1016/j.bcra.2025.100310
Tanvir Rahman , Tanjid Ahmed , Md. Sakibur Rahman , Amreen Hossain , Jannatun Noor
The Network Block Device (NBD) protocol enhances the Android ecosystem's storage management and power efficiency, particularly on ARM devices. The study addresses storage limitations on ARM devices and explores how NBD can provide a solution. By leveraging NBD, Android devices can connect to remote storage resources and expand storage capacity without physical upgrades. This enables Android devices to be used as controllers for IoT networks and smart home appliances. The study includes statistical comparisons of NBD with alternative protocols like secure File Transfer Protocol (sFTP), Internet Small Computer System Interface (iSCSI), Network File System (NFS), Server Message Block (SMB), and Hypertext Transfer Protocol (HTTP). Through read-and-write tests, NBD exhibits superior performance in bandwidth speed and operation duration, with speeds more than twice as fast as other protocols. Furthermore, the evaluation compares NBD's cloud storage capabilities with popular services such as Google Drive, Dropbox, OneDrive, and Google Cloud Platform (GCP). NBD outperforms these services regarding read and write speeds, completing operations much faster. The study also examines NBD's power consumption, demonstrating its energy efficiency compared to other protocols and cloud storage services. NBD's lower power consumption makes it ideal for energy-sensitive Android applications. In conclusion, the integration of NBD into the Android ecosystem enhances efficiency, storage flexibility, and adaptability. It empowers ARM-based Android devices with increased capabilities and versatility.
{"title":"Empirical analysis of Android storage management using Network Block Device (NBD) protocol: A comprehensive performance and efficiency study","authors":"Tanvir Rahman , Tanjid Ahmed , Md. Sakibur Rahman , Amreen Hossain , Jannatun Noor","doi":"10.1016/j.bcra.2025.100310","DOIUrl":"10.1016/j.bcra.2025.100310","url":null,"abstract":"<div><div>The Network Block Device (NBD) protocol enhances the Android ecosystem's storage management and power efficiency, particularly on ARM devices. The study addresses storage limitations on ARM devices and explores how NBD can provide a solution. By leveraging NBD, Android devices can connect to remote storage resources and expand storage capacity without physical upgrades. This enables Android devices to be used as controllers for IoT networks and smart home appliances. The study includes statistical comparisons of NBD with alternative protocols like secure File Transfer Protocol (sFTP), Internet Small Computer System Interface (iSCSI), Network File System (NFS), Server Message Block (SMB), and Hypertext Transfer Protocol (HTTP). Through read-and-write tests, NBD exhibits superior performance in bandwidth speed and operation duration, with speeds more than twice as fast as other protocols. Furthermore, the evaluation compares NBD's cloud storage capabilities with popular services such as Google Drive, Dropbox, OneDrive, and Google Cloud Platform (GCP). NBD outperforms these services regarding read and write speeds, completing operations much faster. The study also examines NBD's power consumption, demonstrating its energy efficiency compared to other protocols and cloud storage services. NBD's lower power consumption makes it ideal for energy-sensitive Android applications. In conclusion, the integration of NBD into the Android ecosystem enhances efficiency, storage flexibility, and adaptability. It empowers ARM-based Android devices with increased capabilities and versatility.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"7 1","pages":"Article 100310"},"PeriodicalIF":5.6,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079269","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}
Pub Date : 2025-12-01DOI: 10.1016/j.bcra.2025.100293
Munkenyi Mukhandi , Jorge Granjal , João P. Vilela
We introduce a novel blockchain-based interledger authorisation scheme, a unique solution designed to support delegated authorisation management in cross-domain cloud environments. This innovative approach enables client applications, acting on behalf of a user, to request access to specific resources owned by a different organization. It benefits cross-domain multi-cloud applications, such as large-scale collaboration projects involving multiple cloud service providers. Multi-cloud presents authorisation challenges because of complex access control operations in multiple distinct domains. OAuth2 is the state-of-the-art choice for delegated authorisation. However, it falls short in handling such complex interactions with multiple authorisation servers and resource servers, and this is our motivation. Compared with OAuth2, our approach overcomes the limitations of a centralized model and achieves coordinated distinct delegations among multiple entities without a third-party trusted component. authorisation servers are blockchain participants and designated access token issuers, ensuring minimum client data collection and promoting client privacy. Multiple smart contracts are deployed in our multi-ledger blockchain environment to guarantee the provenance of the authorisation operations and facilitate scalable cross-domain authorisation. Our “hybrid interledger model” combines security techniques such as blockchain-based device authentication, hashed time-lock contracts (HTLCs), and service discovery. The blockchain-based device authentication ensures secure and trusted interactions, HTLCs enable time-bound transactions, and service discovery simplifies finding and connecting to the required cloud services. Our experimental evaluation provides insights into the scalability of our approach, which achieves decentralized authorisation in a multi-cloud environment with acceptable latencies compared with related works and shows stable throughput against concurrent authorisation requests in a multi-ledger system.
{"title":"Blockchain hybrid-model scheme for scalable cross-domain authorisation","authors":"Munkenyi Mukhandi , Jorge Granjal , João P. Vilela","doi":"10.1016/j.bcra.2025.100293","DOIUrl":"10.1016/j.bcra.2025.100293","url":null,"abstract":"<div><div>We introduce a novel blockchain-based interledger authorisation scheme, a unique solution designed to support delegated authorisation management in cross-domain cloud environments. This innovative approach enables client applications, acting on behalf of a user, to request access to specific resources owned by a different organization. It benefits cross-domain multi-cloud applications, such as large-scale collaboration projects involving multiple cloud service providers. Multi-cloud presents authorisation challenges because of complex access control operations in multiple distinct domains. OAuth2 is the state-of-the-art choice for delegated authorisation. However, it falls short in handling such complex interactions with multiple authorisation servers and resource servers, and this is our motivation. Compared with OAuth2, our approach overcomes the limitations of a centralized model and achieves coordinated distinct delegations among multiple entities without a third-party trusted component. authorisation servers are blockchain participants and designated access token issuers, ensuring minimum client data collection and promoting client privacy. Multiple smart contracts are deployed in our multi-ledger blockchain environment to guarantee the provenance of the authorisation operations and facilitate scalable cross-domain authorisation. Our “hybrid interledger model” combines security techniques such as blockchain-based device authentication, hashed time-lock contracts (HTLCs), and service discovery. The blockchain-based device authentication ensures secure and trusted interactions, HTLCs enable time-bound transactions, and service discovery simplifies finding and connecting to the required cloud services. Our experimental evaluation provides insights into the scalability of our approach, which achieves decentralized authorisation in a multi-cloud environment with acceptable latencies compared with related works and shows stable throughput against concurrent authorisation requests in a multi-ledger system.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 4","pages":"Article 100293"},"PeriodicalIF":5.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617873","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}
Pub Date : 2025-12-01DOI: 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.
{"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}
Pub Date : 2025-12-01DOI: 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.
{"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}
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.
{"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}
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.
{"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}
Pub Date : 2025-12-01DOI: 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.
{"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}
Pub Date : 2025-12-01DOI: 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.
{"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}
Pub Date : 2025-12-01DOI: 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.
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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.
{"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}
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