Blockchain Papers

Ming Zhou, Zhen Yang, Haiyang Yu, Shui Yu

No abstract is available for this record.

Bimal Ghimire, Danda B. Rawat, Abdul Rahman

With the rise of smart vehicles, an intelligent transportation system intelligent transport system (ITS) learning from the tremendous volume of the data generated by the distributed vehicles is becoming a reality. blockchain (BC)-based federated learning (FL) facilities a highly secure and trustless collaborative learning framework; however, it could be inefficient for the time-sensitive services of the Internet of Vehicles (IoV). In this regard, this study investigates information dissemination delay in BC-based FL for IoV using a small world network-based peer selection strategy. Additionally, we also incorporate IoV specific informed decision for peer selection to facilitate even faster dissemination of information in the network and make BC-based system efficient. Network topology of vehicles is represented using a graph approach and based on that the information dissemination delay is formulated. The delay is compared between scenarios when peer selection strategy uses informed decision and that does not use informed decision. The performance of the proposed approach is evaluated through the graph analysis which demonstrates that the inclusion of informed decision reduces the information dissemination delay remarkably.

Jinrui Sha, Shengli Liu

No abstract is available for this record.

Suman Madan

Background: The immense increase of data due to web services, social media, Health care data, and mobile data results in the massive quantity of organized and unorganized data known as big data, which is utilized by various data miners as it contains some sensitive information. Method: In this research, a privacy mechanism in the decentralized cloud through the smart contract approach is developed to ensure the privacy of the data and ensure a fair trading strategy. Findings: The comparative analysis is revealed in the proposed SABPP model, which shows that the responsiveness attained by the proposed SABPP method is found to be 26.9759sec, 85.2969sec, and 158.6968sec for 20, 60 and 100 nodes respectively. Novelty: In this research, the smart contract approach named SABPP is proposed that ensures the smart agreement trading in the Blockchain and overcomes the privacy challenge associated with the trusted third party thereby, ensuring the data availability for the data consumer and privacy for the data provider. Keywords: Blockchain, smart contract, privacy preservation, authentication, access control, data trading strategy

Chuan Zhang, Mingyang Zhao, Weiting Zhang, Qing Fan · 6 authors

Metaverse provides human-centric immersive communication experiences where humans can teleport across different virtual landscapes and build real-time communications via digital identities with others in the same landscape. Despite great benefits, a natural question in human-centric metaverse communications is how to secure digital content among humans. In this regard, blockchain has been widely applied due to its distinct features (e.g., decentralization, transparency, and immutability). Unfortunately, the inherent properties of the blockchain also hinder humans from further deploying preferences to flexibly govern the digital content (i.e., who can read and who can edit), limiting human-centric communication abilities. Some redactable blockchain-based solutions have been proposed, but most of them suffer from the issues of data and preference leakage. To address the issues, we propose a privacy-preserving identity-based data governance (IDRG) scheme for blockchain-empowered human-centric metaverse communications. Combining digital identities, IDRG cryptographically allows humans to govern readability and editability with the right downward compatibility (i.e., humans with editability are endowed with readability) while protecting policy privacy. Specifically, IDRG leverages the polynomial function technique to break through the bottleneck of the traditional identity-based encryption technique (i.e., a policy only contains a user) to achieve a policy for multiple users. Subsequently, the optimized policies are utilized to enrich chameleon hash-based redactable blockchains for comprehensive rights governance. Further, IDRG supports user accountability and revocation by combining the proxy re-encryption technique. Security analysis proves the security of IDRG under the chosen-ciphertext attack. Experiments on the FISCO blockchain platform demonstrate that IDRG requires approximately 0.1 s to process an encryption request, 0.01 s for a reading request, and 1 s for an editing request. Overall, IDRG achieves a$3\times $reduction in computational costs compared with state-of-the-art solutions.

Yuan Liu, Yanan Zhang, Shen Su, Lejun Zhang · 7 authors

Spatial crowdsourcing (SC) has become a fundamental and emerging technology in Metaverse, facilitating the creation of immersive experiences through location-based services. In these systems, a central SC server leverages SC workers who physically travel to task locations to gather spatiotemporal environment data. However, conventional SC systems face two significant challenges: (1) the SC server, functioning as a centralized authority, can sometimes be unreliable, either due to intentional or unintentional misconduct, (2) to ensure efficient task assignment and validation, the location privacy of tasks and workers is openly accessible. In this study, we formally define location privacy preserved proof generation and verification problem (LP-PGVP) within an SC task matching scenario, with the aim to the above two challenges. Our proposed solution is a blockchain-based SC system (BlockSC), which provides a decentralized platform for task requesters and workers in the Metaverse context through calling smart contracts. We also introduce a ciphertext-based task matching scheme where task location access is granted only to eligible workers executing a task, benefiting from the design of geographic coordinate transformation and bilinear mapping methodology. To further demonstrate the task matching scheme’s operation and impact, we present an easy-to-understand case study. Our evaluation findings confirm that the proposed system effectively maintains location privacy for both SC workers and task requesters, without a considerable sacrifice in task matching efficiency.

Olusogo Popoola, Marcos Rodrigues, Jims Marchang, Alex Shenfield · 6 authors

Protecting private data in smart homes, a popular Internet-of-Things (IoT) application, remains a significant data security and privacy challenge due to the large-scale development and distributed nature of IoT networks. Recently, smart healthcare has leveraged smart home systems, thereby compounding security concerns in terms of the confidentiality of sensitive and private data and by extension the privacy of the data owner. However, PoA-based Blockchain DLT has emerged as a promising solution for protecting private data from indiscriminate use and thereby preserving the privacy of individuals residing in IoT-enabled smart homes. This review elicits some concerns, issues, and problems that have hindered the adoption of blockchain and IoT (BCoT) in some domains and suggests requisite solutions using the aging-in-place scenario. Implementation issues with BCoT were examined as well as the combined challenges BCoT can pose when utilised for security gains. The study discusses recent findings, opportunities, and barriers, and provide recommendations that could facilitate the continuous growth of blockchain application in healthcare. Lastly, the study then explored the potential of using a PoA-based permission blockchain with an applicable consent-based privacy model for decision-making in the information disclosure process, including the use of publisher-subscriber contracts for fine-grained access control to ensure secure data processing and sharing, as well as ethical trust in personal information disclosure, as a solution direction. The proposed authorisation framework could guarantee data ownership, conditional access management, scalable and tamper-proof data storage, and a more resilient system against threat models such as interception and insider attacks.

Wenxian Jiang, Xianglong Lv

Aiming at the existing problems of insufficient security and poor scalability of existing blockchain data management solutions for the Internet of Vehicles, we use IPFS distributed technology to design a data privacy protection method for the Internet of Vehicles based on zero-knowledge proof. First, we use the Schnorr identity authentication protocol, a classic non-interactive zero-knowledge proof scheme, to complete the authentication and authorization of vehicles by RSU under the premise of protecting vehicle privacy. Secondly, we store encrypted data on IPFS-based edge distributed servers, and use Hyperledger Fabric to store authentication records and data indexes, which solves the problem of insufficient blockchain scalability. Finally, in order to improve the controllability and security of the data, we use the proxy re-encryption mechanism to manage the Symmetric-key of the data, and let RSU act as a proxy to perform re-encryption. Compared with the existing schemes, the proposed scheme reduces the communication overhead of the vehicle identity authentication phase, which is only 1728 bits. And while improving the scalability of the blockchain, it also enhances the privacy protection of the data of the Internet of Vehicles.

G. Pavithra, Kunwar Singh

Stake voting is a voting system where the vote cast by a voter is proportional to their account balance/asset. We propose the first implementation of an efficient, fully-decentralized, universally-verifiable stake voting system with perfect voter privacy. Our contribution is two-fold. First, we design a zero knowledge proof (ZKP) for equality of plaintexts of 2 different ciphertexts encrypted under different encryption schemes, one under ElGamal encryption scheme and another under Paillier encryption scheme. We believe that ours is the first ZKP design for this problem statement. Second, we implement a publicly-verifiable Stake voting system using the ZKP design by enforcing perfect privacy to voters and correctness of election results. Our voting system is applicable to many situations like shareholder/stockholder voting in companies. We have also provided the financial and computational breakdown feasibility of our implementation on Ganache local blockchain.

Zhiqi Lei, Keke Gai, Jing Yu, Shuo Wang · 6 authors

In Federated Learning (FL), blockchain has been extensively used to achieve distributed and tamper-resistant data processing. However, typical Blockchain-based Federated Learning (BFL) rarely considers clients’ resource and computing limits. High-capacity clients may be sacrificed when all clients train on the same neural network. This paper proposes a Blockchain-based Heterogeneous Federated Learning (BlocFL) model to address the challenges above. BlocFL replaces the central server with a consortium blockchain, and several neural networks are employed for local training. Considering the challenges in resource allocation in BFL, especially in heterogeneous networks, we propose a consortium blockchain-based heterogeneous federated learning client selection method. The proposed method optimizes the choice of client nodes under the limits of computational resources. Experiment results demonstrate that our method can allocate appropriate neural network models to each client and effectively improve the efficiency of local training in HFL. It also can achieve a comparable level of accuracy to the baseline approach with similar training parameters.

Xuyang Liu, Lanju Kong, Yuehan Su, Chenfei Sun

To alleviate the pressure on storage and execution on blockchain, existing platforms such as Ethereum have designed payment channels, attempting to transfer some of the pressure to off chain. Consistency protocols such as “lock-submit” based on asset are used to ensure consistency between on chain and off chain. However, the increasing number of multi-property-right and multi-attribute assets pose challenges to the parallel performance of existing payment channels. This paper proposes an on chain and off chain consistency protocol for multi-attribute digital assets based on data property rights. Firstly, we use a hypergraph to store asset contents off chain. Also, we use an index MMI (multi-property-right and multi-attribute index) on chain to store the relationship between accounts and assets, partial information of assets. Secondly, a multiparty payment channel is opened, verifiers verify the legitimacy of the transaction request based on the attribute state list in MMI and allow collaborative attribute modification on and off chain. Finally, nodes merge assets based on asset version numbers to ensure the consistency and security of asset content. After experiments, our consistency protocol has a success rate of 99.68% after asset merging, and the performance of execution can be improved by about 14%-29%, throughput can be improved by about 6%-14%, and the transaction size in the block is smaller.

Chenhao Zhang, Jiameng Cheng, Hongwei Zhang, Jinsong Wang · 5 authors

Within the context of the Industrial Internet, data has emerged as an increasingly critical asset in the domains of enterprise production, operation, and management, thereby solidifying its role as a pivotal determinant of competitive advantage for corporate entities. Nonetheless, the intrinsic characteristics of Industrial Internet data, characterized by its diverse origins, substantial volumes, and intricate privacy considerations, have given rise to issues surrounding the unambiguous establishment of data rights and inadvertent disclosure of sensitive information throughout the processes of data propagation and value transmission. To address these multifaceted challenges, this paper introduces a systematic framework for data rights verification, one that incorporates the utilization of Non-Fungible Tokens (NFTs) equipped with a secure locking mechanism in conjunction with adaptive federated learning. This proposed framework bifurcates the data rights verification process into two distinctive phases: data ownership verification and validation of data usage rights. Through the meticulous implementation of smart contracts and the adept utilization of the locking mechanism inherent within NFTs, the framework effectively dissects the intricacies of data rights, thereby ensuring contemporaneousness in data utilization and enabling controlled access. Furthermore, in the phase dedicated to the validation of data usage rights, we introduce an approach firmly rooted in the principles of adaptive federated learning. Leveraging the FedMGDA+ algorithm for distributed storage and computation, this approach successfully validates data usage rights. Empirical findings substantiate the significant advantages encapsulated within this framework, particularly in the domains of data and identity security. Notably, this framework maintains robust precision and scalability throughout the process of data rights verification for distributed model training, thereby exhibiting commendable performance in this intricate domain.

Hwei‐Chi Chong, K. L. Eddie Law

In recent years, the technologies of blockchains, the Internet of Things (IoT), etc. technologies have been drawing attention across different industries. In our experience, during a pandemic, we look for innovations and personalization of secure data sharing on Electronic Health Records (EHRs) to provide better healthcare services. In the paper, we propose a decentralized record management system which is to share data over multiple independent blockchain entities. Each blockchain runs under the administration of an independent healthcare organization. In our design, data would be shared and integrated among multiple Hospital Information Systems (HIS) across different healthcare organizations. It gives doctors and healthcare personnel an easy and safe way to obtain the health records of patients across hospitals dynamically worldwide through negotiated Service-Layer Agreements (SLAs) to provide accurate medical services. Our system leverages blockchain properties to manage access authentication, retrieve medical data, and add new patient data entries. Without a centralized system and database, the design autonomously, dynamically, and securely governs the retrieval and storage of data traffic based on the SLAs. Further, we integrate the system design with the Bell-LaPadula access control model to maintain the confidentiality of security organized in a non-discretionary fashion for different layers of secrecy. Since an HIS runs within the security bounds of a healthcare authority, we can adopt the Proof-of-Authority (PoA) consensus algorithm, which is developed by the Go Ethereum (Geth) team. The PoA provides an efficient, low computational power consumption approach for securely validating the blockchains.

Aleksandr Kormiltsyn, Vimal Dwivedi, Chibuzor Udokwu, Alex Norta

Integrating personal health records (PHRs) and electronic health records (EHRs) facilitates the provision of novel services to individuals, researchers, and healthcare practitioners. Simultaneously, integrating healthcare data leads to complexities arising from the structural and semantic heterogeneity within the data. The subject of healthcare data evokes strong emotions due to concerns surrounding privacy breaches. Blockchain technology is employed to address the issue of patient data privacy in inter-organizational processes, as it facilitates patient data ownership and promotes transparency in its usage. At the same time, blockchain technology creates new challenges for e-healthcare systems, such as data privacy, observability, and online enforceability. This article proposes designing and formalizing automatic conflict resolution techniques in decentralized e-healthcare systems. The present study expounds upon our concepts by employing a running case study centered around preventive and personalized healthcare domains. Plain Language Summary: This paper suggests using blockchain technology for privacy concerns in integrating personal health records and electronic health records in decentralized e-healthcare systems. This report focuses on designing automatic conflict resolution techniques to ensure patient data ownership, transparency, and privacy in inter-organizational processes. This paper proposes designing automatic conflict resolution techniques in decentralized e-healthcare systems, which can improve inter-organizational processes in healthcare. Using blockchain technology to integrate personal and electronic health records can ensure patient data ownership and promote transparency in data usage, addressing privacy concerns in healthcare systems. This paper emphasizes the importance of data privacy and protection in healthcare systems, highlighting the need for compliance with laws and regulations. The research results, including the proof-of-concept prototype, can provide practical insights into implementing conflict resolution techniques in decentralized e-healthcare systems.

Yang Luding, Wang Jiahao

Edge computing in IoT has garnered significant attention due to its potential to address the limitations of terminal devices and offer advantages such as lower energy consumption and reduced latency compared to centralized cloud computing systems. However, the lack of cooperation and trust among different entities in edge networks makes it challenging to establish secure and reliable data sharing environments, necessitating the development of tailored access control mechanisms. This paper suggests a decentralized, distributed end-centric access control model for edge computing networks, integrating the IPFS, smart contract and CP-ABE technology. The proposed model aims to achieve fine-grained access control over data, address potential dishonest search results, and enhance user access management in untrusted environments. This approach is beneficial for IoT communication and data exchange and effectively reduces communication and computational expenses.

Ashutosh Kumar, Garima Verma

Data is often stored as ciphertext on cloud servers to maintain privacy and security. A third-party access key and intervention are required if a data user wants to access encrypted data. A fraudulent third party, however, will jeopardize the system's security. A blockchain-based enhanced secure cloud storage access system was presented to address this issue. We achieve a novel technique by combining Ethereum blockchain technology and ciphertext-policy attribute-based encryption with a reduced attribute string. There is no reliance on a trusted third party for the suggested cloud storage architecture. Our plan contains three essential components. Our technique is superior and more viable based on processing cost, encryption, and decryption time.

Dongkun Hou, Jie Zhang

Federated recommendation systems (FRecSys) alleviate the privacy issues of recommendation systems (RecSys) by distributing model training tasks onto users’ local devices. However, they still need a single global server to aggregate training results from users and, thereby are vulnerable to server malfunctioning. Besides, they assume all users voluntarily use their data and computing resources to train recommendation model gradients, which is usually impractical. This paper aims to address the aforementioned problems of FRecSys using blockchain. A blockchain-based federated matrix factorization is designed and realized for RecSys, named BFRecSys. It eliminates the need for a single central server by storing the items and user matrices of the matrix factorization in a blockchain. An incentive mechanism is designed and implemented via smart contracts to record participants’ contributions. Besides, to further enhance the fairness of the incentive mechanism, a fake gradients detection mechanism based on an unsupervised cluster is designed to evict fake gradients in each iteration. The prototype of BFRecSys is realized, and experiments are carried out on public MovieLens datasets and private Ethereum blockchain. The results show that BFRecSys can significantly improve recommendation performance in terms of training accuracy.

M. Zhao, Chunjing Shi, Yixiao Yuan

The industrial internet of things (IIoT) necessitates robust cross-domain authentication to secure sensitive on-site equipment data. This paper presents a refined reputation-based lightweight consensus mechanism (LRBCM) tailored for IIoT's distributed network structures. Leveraging node reputation values, LRBCM streamlines ledger consensus, minimizing communication overhead and complexity. Comparative experiments show LRBCM outperforms competing mechanisms. It maintains higher throughput as the number of participating nodes increases and achieves a throughput approximately 10.78% higher than ReCon. Moreover, runtime analysis demonstrates LRBCM's scalability, surpassing ReCon by approximately 12.79% with equivalent nodes and transactions. In addition, as a combination of LRBCM, the proposed distributed lightweight authentication mechanism (ELAM) is rigorously evaluated against the security of various attacks, and its resilience is confirmed. Experiments show that ELAM has good efficiency while maintaining high security.

Md Jobair Hossain Faruk, Jim Basney, Jerry Cheng

Managing and exchanging sensitive information securely is a paramount concern for different domains such as scientific, finance, cybersecurity, and healthcare. The increasing reliance on computing workflows and digital data transactions requires ensuring that sensitive information is protected from unauthorized access, tampering, or misuse and ensuring data integrity and transparency. To address this need, several approaches have been proposed such as JWT, SciTokens, Verifiable Credentials, and Smart Contracts which provide different methods for managing and exchanging information securely in centralized or decentralized and trustworthy environments. However, each technology offers unique advantages and limitations that require a comprehensive analysis to understand its potential and challenges. In our previous study, we conducted a comprehensive analysis of these approaches for authenticating and securing access to scientific data. This research further proposes a novel blockchain-based verifiable credentials that integrate the concept of Smart Contracts. The aim of this study is to introduce a decentralized and privacy-preserving authentication mechanism to enable stakeholders to share, verify, or revocation of their data with enhanced security, transparency, and trust. The proposed framework utilizes two different blockchain frameworks, Hyperledger Fabric and Ethereum to conduct comprehensive research to evaluate the effectiveness of both frameworks for the development of verifiable credentials. Our analysis indicates that Hyperledger Fabric offers enhanced security and ensures robust integrity through a private network and chaincode mechanism for authentication and access to data. As a result of our analysis, we adopt Hyperledger Fabric for the implementation and demonstration of the final version of our framework. We evaluate the proposed approach with a set of educational data to measure the effectiveness of the system. We find the proposed framework enables users to share data effectively within a secure network and only authorized stakeholders are allowed to access the shared data.

Nan Xiao, Zhaoshun Wang, Xiaoxue Sun, Junfeng Miao

To address challenges in digital evidence collection and responsibility determination for industrial safety accidents involving industrial Internet of Things (IIoT) device nodes, this paper proposes a blockchain-based digital forensic scheme within the IIoT communication architecture. The scheme utilizes a decentralized blockchain storage mechanism to enable remote storage of digital forensic data. Additionally, it leverages smart contract mechanisms to facilitate efficient retrieval and tracing of related evidence chains. To enhance data security of IIoT device nodes, a token mechanism is implemented for access control. Moreover, to meet real-time evidence acquisition requirements in IIoT, an efficient batch consensus mechanism is proposed. Experimental simulations demonstrate the superiority of the novel consensus algorithm compared to the traditional Delegated Proof-of-Stake (DPOS) consensus in the proposed scheme for the IIoT environment. It meets speed requirements for evidence collection, ensuring tamper-proof, non-repudiable, and permanent storage of digital forensic data. Consequently, the application of blockchain technology for judicial access and evidence storage has made significant contributions to digital forensics within the IIoT context.

Anto Benedetti, Tiphaine Henry, Sara Tucci-Piergiovanni

Blockchain applications are witnessing rapid evolution, necessitating the integration of upgradeable smart contracts. Software patterns have been proposed to summarize upgradeable smart contract best practices. However, research is missing on the comparison of these upgradeable smart contract patterns, especially regarding gas costs related to deployment and execution. This study aims to provide an in-depth analysis of gas costs associated with two prevalent upgradeable smart contract patterns: the Proxy and diamond patterns. The Proxy pattern utilizes a Proxy pointing to a logic contract, while the diamond pattern enables a Proxy to point to multiple logic contracts. We conduct a comparative analysis of gas costs for both patterns in contrast to a traditional non-upgradeable smart contract. We derive from this analysis a theoretical contribution in the form of two consolidated blockchain patterns and a corresponding decision model. By so doing we hope to contribute to the broader understanding of upgradeable smart contract patterns.

Manas Ranjan Lenka, Pinaki Sankar Chatterjee, Niranjan Kumar Ray

As the Internet of Things (IoT) grows, it is essential to provide safe and effective access control mechanisms for IoT devices. The modern smart contract-based access control techniques for the Internet of Things are thoroughly investigated in this research. We systematically review and categorize the existing literature, highlighting the key methodologies, protocols, and architectures proposed in this domain. The study explores how smart contract-based strategies might be used to solve the particular security issues that arise in IoT environments, discussing both the benefits and drawbacks of such a method. We also looked at various methods used in these systems, such as identity management, attribute-based access control, and role-based access control. Additionally, the survey investigates the integration of smart contracts with blockchain technology, emphasizing its impact on security, privacy, and scalability. We also outline the unresolved issues and potential areas for further study in this area, offering both scholars and practitioners insightful information. Overall, this survey offers a comprehensive overview of smart contract-based access control mechanisms for IoT, fostering a deeper understanding of the current advancements and paving the way for future advancements in securing IoT ecosystems.

Lang Wu, Weijian Ruan, Jinhui Hu, Yaobin He

Federated learning (FL) and blockchains exhibit significant commonality, complementarity, and alignment in various aspects, such as application domains, architectural features, and privacy protection mechanisms. In recent years, there have been notable advancements in combining these two technologies, particularly in data privacy protection, data sharing incentives, and computational performance. Although there are some surveys on blockchain-based federated learning (BFL), these surveys predominantly focus on the BFL framework and its classifications, yet lack in-depth analyses of the pivotal issues addressed by BFL. This work aims to assist researchers in understanding the latest research achievements and development directions in the integration of FL with blockchains. Firstly, we introduced the relevant research in FL and blockchain technology and highlighted the existing shortcomings of FL. Next, we conducted a comparative analysis of existing BFL frameworks, delving into the significant problems in the realm of FL that the combination of blockchain and FL addresses. Finally, we summarized the application prospects of BFL technology in various domains such as the Internet of Things, Industrial Internet of Things, Internet of Vehicles, and healthcare services, as well as the challenges that need to be addressed and future research directions.

Jie Cui, Yatao Li, Qingyang Zhang, Hong Zhong · 6 authors

There is a growing concern about the complete lifecycle security of data in Internet of Things (IoT). This may cause privacy and trust problems for users regarding data sources, data storage, and access control for data sharing. Blockchain is a valuable solution to the above problems through distributed ledger technology, and it has been widely applied in various fields such as public services, finance, and IoT. However, the data in IoT are characterized by a large quantity, large capacity, and timely response, and existing blockchain systems only partially resolve them for data security and performance. We propose DSChain for IoT data security to address the challenges mentioned above. Our system uses a certificateless signature to ensure a trusted data source and public auditing to ensure the integrity of stored data while using ciphertext-policy attribute-based encryption to control access to shared data. Moreover, we propose a packaging mechanism based on the Merkle Hash Tree that effectively improves system performance. We implement the DSChain and provide a detailed analysis of performance and security. The experimental results indicate that DSChain can achieve approximately 1,035 transactions per second on a single peer and is scalable.