Permissioned Blockchain Research Articles

A Systematic Review of Fast, Scalable, and Efficient Hardware Implementations of Elliptic Curve Cryptography for Blockchain

Blockchain technology entered the enterprise domain under the name of permissioned blockchains and hybrid or verifiable database systems, as they provide a distributed solution that allows multiple distrusting parties to share common information. One drawback of these systems is the overhead added by the cryptographic functions which impacts the throughput in terms of transactions per second and increases the latency of transaction processing. Many of the cryptographic functions and protocols used in blockchains are based on Elliptic Curve Cryptography (ECC). Unfortunately, ECC operations such as modulo inverse or scalar point multiplication have considerable latency which causes the slowdown of the entire system. In such situations, reconfigurable computing architectures, such as FPGAs, can be used to offload these tasks to overcome the performance loss. This survey analyzes the current state-of-the-art designs and implementations of ECC from a hardware perspective. We use a PRISMA-based approach to filter recent publications and to reduce their number from over 16,000 to only 43 highly relevant designs. In the end, we show that very few designs are able to fulfill all three properties of high performance, scalability, and efficiency.

Appropriately matching transport care units to patients in an interhospital Transport Care: an implementation report.

In interfacility transport care, a critical challenge exists in accurately matching ambulance response levels to patients' needs, often hindered by limited access to essential patient data at the time of transport requests. Existing systems cannot integrate patient data from sending hospitals' electronic health records (EHR) into the transfer request process, primarily due to privacy concerns, interoperability challenges, and the sensitive nature of EHR data. We introduce a distributed digital health platform, Interfacility Transport Care (ITC)-InfoChain, designed to solve this problem without compromising EHR security or data privacy. This report details the implementation of Interfacility Transport Care (ITC)-InfoChain, a secure, blockchain-based platform designed to enhance real-time data sharing without compromising data privacy or EHR security. The ITC-InfoChain platform prototype was implemented on AWS cloud infrastructure, employing Hyperledger Fabric as a permissioned blockchain. Key elements included participant registration, identity management, and patient data collection isolated from the sending hospital's EHR system. The client program submits encrypted patient data to a distributed ledger, accessible to the receiving facility's critical care unit at the time of transport request and EMS teams during transport through the PatienTrack web application. Performance was evaluated through KPIs such as data transaction times and scalability across transaction loads. The ITC-InfoChain demonstrated strong performance and scalability. Data transaction times averaged 3.1 seconds for smaller volumes (1-20 transactions) and 6.4 seconds for 100 transactions. Optimized configurations improved processing times to 1.8-1.9 seconds for 400 transactions. These results confirm the platform's capacity to handle high transaction volumes, supporting timely, real-time data access for decision-making during transport requests and patient transfers. The ITC-InfoChain platform addresses the challenge of matching appropriate transport units to patient needs by ensuring data privacy, integrity, and real-time data sharing, enhancing coordination of patient care. The platform's success suggests potential for regional pilots and broader adoption in secure healthcare systems. Stakeholder resistance due to blockchain unfamiliarity and data privacy concerns remains. Funding has been sought to support a pilot program to address these challenges through targeted education and engagement.

Dynamic-EC: an efficient dynamic erasure coding method for permissioned blockchain systems

Dynamic-EC: an efficient dynamic erasure coding method for permissioned blockchain systems

Reducing clients’ influence in property valuation: An exploration of a blockchain-based solution

Clients' influence remains a significant issue in the property valuation industry, particularly in emerging countries like Nigeria, where existing solutions have proven ineffective. This study, therefore, considers blockchain technology as a medium for delivering information transparency and explores the application of a blockchain-based tool for reducing clients' influence in property valuation. Specifically, this study is pioneering in proposing, developing, and testing a blockchain-based solution for reducing client influence in property valuation, suggesting a promising avenue for increasing transparency in the process. This study involves several stages. Firstly, propchain, a blockchain-based mobile application, was developed and deployed on the Hyperledger Fabric Network, a permissioned blockchain network. The efficacy of the proposed solution was qualitatively tested by a single-round focus group held with valuers, bankers, and a loan customer who used the application to simulate a property valuation exercise for a mortgage. The findings suggest that blockchain technology could be a viable tool for reducing client influence in property valuations. However, specific challenges in the Nigerian context, such as data access, information verification, and stakeholder trust, present significant obstacles. These issues highlight the need for robust institutional support systems to enhance the efficacy of blockchain solutions in this domain. This study supports Levy and Schuck's (2005) assertion that increased information transparency can reduce client influence. Nevertheless, our research indicates that the successful implementation of blockchain in property valuation will require overcoming systemic barriers unique to the Nigerian environment. The implication of key findings is also discussed.

Transactional dynamics in hyperledger fabric: A stochastic modeling and performance evaluation of permissioned blockchains

Blockchain, often integrated with distributed systems and security enhancements, has significant potential in various industries. However, environmental concerns and the efficiency of consortia-controlled permissioned networks remain critical issues. We use a Stochastic Petri Net model to analyze transaction flows in Hyperledger Fabric networks, achieving a 95% confidence interval for response times. This model enables administrators to assess the impact of system changes on resource utilization. Sensitivity analysis reveals major factors influencing response times and throughput. Our case studies demonstrate that block size can alter throughput and response times by up to 200%, underscoring the need for performance optimization with resource efficiency.

BlockLoader: A Comprehensive Evaluation Framework for Blockchain Performance Under Various Workload Patterns

Hyperledger Fabric is one of the most popular permissioned blockchain platforms widely adopted in enterprise blockchain solutions. To optimize and fully utilize the platform, it is desired to conduct a thorough performance analysis of Hyperledger Fabric. Although numerous studies have analyzed the performance of Hyperledger Fabric, three significant limitations still exist. First, existing blockchain performance evaluation frameworks rely on fixed workload rates, which fail to accurately reflect the performance of blockchain systems in real-world application scenarios. Second, the impact of extending the breadth and depth of endorsement policies on the performance of blockchain systems has yet to be adequately studied. Finally, the impact of node crashes and recoveries on blockchain system performance has yet to be comprehensively investigated. To address these limitations, we propose a framework called BlockLoader, which offers seven different distributions of load rates, including linear, single-peak, and multi-peak patterns. Next, we employ the BlockLoader framework to analyze the impact of endorsement policy breadth and depth on blockchain performance, both qualitatively and quantitatively. Additionally, we investigate the impact of dynamic node changes on performance. The experimental results demonstrate that different endorsement policies exert distinct effects on performance regarding breadth and depth scalability. In the horizontal expansion of endorsement policies, the OR endorsement policy demonstrates stable performance, fluctuating around 88 TPS, indicating that adding organizations and nodes has minimal impact. In contrast, the AND endorsement policy exhibits a declining trend in performance as the number of organizations and nodes increases, with an average decrease of 10 TPS for each additional organization. Moreover, the dynamic behaviour of nodes exerts varying impacts across these endorsement policies. Specifically, under the AND endorsement policy, dynamic changes in nodes significantly affect system performance. The TPS of the AND endorsement policy shows a notable decline, dropping from 79.6 at 100 s to 41.96 at 500 s, reflecting a reduction of approximately 47% over time. Under the OR endorsement policy, the system performance remains almost unaffected.

[formula omitted]: A blockchain-based secure access control management for the Internet of Things

The Internet of Things (IoT) paradigm has widespread applications across many fields in which private and sensitive user or environmental data are sensed and shared. Most present-day IoT applications depend on centralized cloud servers for authentication and access control. Validating the identity of a user and determining the legitimacy of his/her access requests require multiple rounds of data communications over the untrusted Internet, exposing sensitive data to potential attacks. Thus, protecting these data from security and privacy attacks and ensuring legitimate access is imperative. To address this challenge, we adopt an emerging technology called blockchain to propose a decentralized security framework called BloAC. It ensures secure access control in IoT networks without the intervention of the back-end cloud. We have used the Hyperledger Fabric, an open-source, permissioned blockchain platform, for implementing a prototype system using customized attribute-based access control (ABAC) policies. We have performed simulated and real test bed-based experiments to illustrate that BloAC outperforms the cloud–server-based access control in latency and scalability, significantly reducing latency by up to 42.45% compared to cloud-based solutions. Finally, we conduct a security analysis to formally verify the ABAC policies used in BloAC and establish its robustness against attacks theoretically and using the AVISPA tool.

A Scalable, Secure, and Efficient Framework for Sharing Electronic Health Records Using Permissioned Blockchain Technology

This paper presents a scalable, secure blockchain-based healthcare system architecture that efficiently manages large patient datasets. DHTs and Skip Lists enable efficient data access, while DPoS and PBFT facilitate parallel transaction processing. Adaptive filters, Radix Trees extended by Merkle Trees, and an immutable blockchain ledger secured by Tendermint consensus ensure data integrity and protection against evolving threats. Threshold Cryptography secures consensus participant selection, and Bulletproofs verify transactions, complying with healthcare regulations. ChaCha20, a symmetric stream cipher, encrypts sensitive data, enhancing performance across devices. ABAC manages access rights, ensuring fine-grained control over data accessibility. This architecture offers a comprehensive, efficient, and secure solution for healthcare data management in blockchain environments.

An efficient Proof-of-Authority consensus scheme against cloning attacks

Proof-of-Authorization (PoA) consensus algorithms are widely used in permissioned blockchain networks due to their high throughput, security, and efficiency. However, PoA is susceptible to cloning attacks, where attackers copy the authenticator identity and key, thereby compromising the consensus integrity. This study proposes a novel randomized authenticator within the PoA framework to mitigate cloning attacks and solve the leader selection bottleneck. The main contributions include 1) Introducing unpredictability in leader selection through Verifiable Random Functions (VRFs) to prevent identity duplication.2) Dynamic group management using a hierarchical decentralized architecture of distributed ledgers that balances security and performance.3) Using threshold signatures to avoid a single point of failure among validators.4) Comprehensively analyzing attacks, security, randomness, and availability.5) Evaluating the effectiveness of a randomized authenticator by means of OMNET++ simulations to assess efficiency. By integrating randomness into leader selection and robust consensus design, the approach enables reliable and secure dynamic group management in decentralized networks.

Secure and Transparent Lung and Colon Cancer Classification Using Blockchain and Microsoft Azure

Background: The global healthcare system faces challenges in diagnosing and managing lung and colon cancers, which are significant health burdens. Traditional diagnostic methods are inefficient and prone to errors, while data privacy and security concerns persist. Objective: This study aims to develop a secure and transparent framework for remote consultation and classification of lung and colon cancer, leveraging blockchain technology and Microsoft Azure cloud services. Dataset and Features: The framework utilizes the LC25000 dataset, containing 25,000 histopathological images, for training and evaluating advanced machine learning models. Key features include secure data upload, anonymization, encryption, and controlled access via blockchain and Azure services. Methods: The proposed framework integrates Microsoft Azure’s cloud services with a permissioned blockchain network. Patients upload CT scans through a mobile app, which are then preprocessed, anonymized, and stored securely in Azure Blob Storage. Blockchain smart contracts manage data access, ensuring only authorized specialists can retrieve and analyze the scans. Azure Machine Learning is used to train and deploy state-of-the-art machine learning models for cancer classification. Evaluation Metrics: The framework’s performance is evaluated using metrics such as accuracy, precision, recall, and F1-score, demonstrating the effectiveness of the integrated approach in enhancing diagnostic accuracy and data security. Results: The proposed framework achieves an impressive accuracy of 100% for lung and colon cancer classification using DenseNet, ResNet50, and MobileNet models with different split ratios (70–30, 80–20, 90–10). The F1-score and k-fold cross-validation accuracy (5-fold and 10-fold) also demonstrate exceptional performance, with values exceeding 99.9%. Real-time notifications and secure remote consultations enhance the efficiency and transparency of the diagnostic process, contributing to better patient outcomes and streamlined cancer care management.

Permissioned blockchain network for proactive access control to electronic health records

BackgroundAs digital healthcare services handle increasingly more sensitive health data, robust access control methods are required. Especially in emergency conditions, where the patient’s health situation is in peril, different healthcare providers associated with critical cases may need to be granted permission to acquire access to Electronic Health Records (EHRs) of patients. The research objective of this work is to develop a proactive access control method that can grant emergency clinicians access to sensitive health data, guaranteeing the integrity and security of the data, and generating trust without the need for a trusted third party.MethodsA contextual and blockchain-based mechanism is proposed that allows access to sensitive EHRs by applying prognostic procedures where information based on context, is utilized to identify critical situations and grant access to medical data. Specifically, to enable proactivity, Long Short Term Memory (LSTM) Neural Networks (NNs) are applied that utilize patient’s recent health history to prognose the next two-hour health metrics values. Fuzzy logic is used to evaluate the severity of the patient’s health state. These techniques are incorporated in a private and permissioned Hyperledger-Fabric blockchain network, capable of securing patient’s sensitive information in the blockchain network.ResultsThe developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism within the blockchain network proved to be a robust tool to enhance the performance of the access control mechanism. Furthermore, the blockchain network of this work can record the history of who and when had access to a specific patient’s sensitive EHRs, guaranteeing the integrity and security of the data, as well as recording the latency of this mechanism, where three different access control cases are evaluated. This access control mechanism is to be enforced in a real-life scenario in hospitals.ConclusionsThe proposed mechanism informs proactively the emergency team of professional clinicians about patients’ critical situations by combining fuzzy and predictive machine learning techniques incorporated in the private and permissioned blockchain network, and it exploits the distributed data of the blockchain architecture, guaranteeing the integrity and security of the data, and thus, enhancing the users’ trust to the access control mechanism.

Inventory pledge financing decisions based on a permissioned blockchain by controlling fraudulent risk

Inventory pledge financing (IPF) is a crucial financing way for small and medium-sized enterprise (SMEs). But banks are reluctant to finance SMEs due to fraudulent risk in practice. This paper discusses the application of blockchain in IPF, particularly its impact on mitigating fraud risks. Utilizing game theory models, we illustrate how the finance and operation decisions of participants, along with supply chain efficiency, are influenced by the introduction of blockchain. Meanwhile, equilibrium outcomes are analysed and numerical study is given. Our analysis reveals that under certain conditions, blockchain integration can lead to reduced loan interest rates, lower wholesale prices, increased order quantities by buyers, and enhanced supply chain efficiency. Lastly, we develop a protocol to demonstrate the transfer of digital warehouse receipt on a permissioned blockchain to avoid fraudulent risk. This study provides a theoretical foundation, and a guidance for decisions-making in blockchain-enabled IPF schme.

Concordit: A credit-based incentive mechanism for permissioned redactable blockchain

Malicious attacks and the introduction of illegal data put blockchains at risk, and blockchain governance is gaining increasing attention. The redactable blockchain technology has become a mainstream solution for blockchain governance. However, a low completion rate for redaction tasks limits current redactable blockchain technologies, primarily due to the absence of an effective incentive mechanism for participants. This gap underscores the urgent need for designing and implementing robust incentive mechanisms in redactable blockchains. Incentive mechanisms can motivate and guide entities to participate and perform desired behaviors through awards and punishments. This paper proposes Concordit, the first deployable credit-based incentive mechanism for redactable blockchains. Its purpose is to encourage submitters to submit legal redaction requests, modifiers to perform legal redaction operations, and verifiers to maintain the behavior consistent with the consensus algorithm. In the context of permissioned blockchains, Concordit utilizes a credit value system for awards and punishments. Additionally, we use a game theory-based mechanism to analyse and model participants’ behavior utilities in the redactable blockchain. Meanwhile, we evaluate the credibility of nodes by combining their static initial credit values and dynamic behavior-related credit values. This system prioritizes high-credibility nodes as participants, thereby enhancing the completion rate for redaction tasks. Finally, the implementation and performance evaluation of our Concordit incentive mechanism demonstrate its effectiveness and practicality.

Emergency Medical Access Control System Based on Public Blockchain

IT has made significant progress in various fields over the past few years, with many industries transitioning from paper-based to electronic media. However, sharing electronic medical records remains a long-term challenge, particularly when patients are in emergency situations, making it difficult to access and control their medical information. Previous studies have proposed permissioned blockchains with limited participants or mechanisms that allow emergency medical information sharing to pre-designated participants. However, permissioned blockchains require prior participation by medical institutions, and limiting sharing entities restricts the number of potential partners. This means that sharing medical information with local emergency doctors becomes impossible if a patient is unconscious and far away from home, such as when traveling abroad. To tackle this challenge, we propose an emergency access control system for a global electronic medical information system that can be shared using a public blockchain, allowing anyone to participate. Our proposed system assumes that the patient wears a pendant with tamper-proof and biometric authentication capabilities. In the event of unconsciousness, emergency doctors can perform biometrics on behalf of the patient, allowing the family doctor to share health records with the emergency doctor through a secure channel that uses the Diffie-Hellman (DH) key exchange protocol. The pendant’s biometric authentication function prevents unauthorized use if it is stolen, and we have tested the blockchain’s fee for using the public blockchain, demonstrating that the proposed system is practical.

P-Chain: Towards privacy-aware smart contract using SMPC

Smart contract, as the representative application of blockchain, has recently fueled extensive research interests from both academia and industry. However, with its wide applications, the weaknesses of smart contract have been gradually revealed. The major barrier to the widespread adoption of smart contract involves concerns about on-chain privacy which refers to the details of input/output privacy. To address privacy concerns, we propose in this paper, P-Chain, a privacy-aware framework for smart contracts of permissioned blockchain to protect sensitive data of users based on Secure Multi-party Computation (SMPC). Unlike existing work that suffer several key drawbacks, including introducing a third party who could get the details of the deal, and high overhead for on-chain and off-chain communication, as well as lacking a privacy protection for output data, we enhance the privacy protection for smart contracts system by adding a new secure multi-party computation layer in P-Chain. Through secure multi-party computing, sensitive inputs of smart contracts are divided into multiple sub-inputs and sent to computing participants for operation respectively, which ensures that each participant can only access part of the user’s information. A stochastic strategy based on (t;n) threshold secret sharing to select calculating parties is also been proposed, which makes it difficult for an attacker to aggregate t of n participants for launching a collusive attack. In addition, we propose the output privacy protection method that makes it possible to reach a consensus without the need to know the output. The extensive experimental evaluation and analysis demonstrate that our scheme enjoys the advantages of calculation correctness, input–output privacy as well as anti-collusion.

CoralDB: A Collaborative Database for Data Sharing Based on Permissioned Blockchain

CoralDB: A Collaborative Database for Data Sharing Based on Permissioned Blockchain

Prediction of permissioned blockchain performance for resource scaling configurations

Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability resorts to try-and-error. A key challenge is that BaaS is often perceived as a “black-box,” leading to uncertainties in performance and resource provisioning. Previous studies attempted to address this challenge; however, the impacts of both vertical and horizontal scaling remain elusive. To this end, we present machine learning-based models to predict network reliability and throughput based on scaling configurations. In our evaluation, the models exhibit prediction errors of ∼1.9%, which is highly accurate and can be applied in the real-world.

Fake Product Detection with Blockchain Technology

Consumers and brands are at serious risk due to the growth of counterfeit goods, especially in regions like Nigeria. Conventional techniques, such border inspections and market raids by the Standards Organization of Nigeria (SON), are inadequate for detecting counterfeit goods. To ensure traceability, transparency, and immutability in the supply chain, this article suggests utilizing blockchain technology. The decentralized and encrypted characteristics of blockchain, when bolstered by smart contracts, enable efficient product tracking from producers to end users, hence impeding the infiltration of fake goods. Using a permissioned blockchain network, this system attempts to confirm the legitimacy of products at every point along the supply chain—manufacturers, distributors, retailers, and end users. The Remix IDE is used to deploy and test Ethereum-based smart contracts that were created in Solidity for the proposed system. This blockchain-based strategy aims to decrease the spread of counterfeit goods, protect consumer confidence, and preserve brand reputation. To offer a user-friendly interface for wider accessibility, future advancements will link this system with decentralized apps (DApps).

Reshaping FinTech with Blockchain Technologies

Abstract: This comprehensive article explores the transformative potential of blockchain technology in the FinTech sector, addressing current challenges and opportunities. It examines the evolving landscape of FinTech, discusses supply chain inefficiencies, administrative overheads, and error-prone systems, and presents blockchain as a solution to these issues. The article delves into the benefits of permissioned blockchains, the importance of scalability and interoperability, and the role of blockchain in building trust-based models. It also covers ROI predictions, implementation strategies, regulatory considerations, and future trends. Through case studies and best practices, the article provides insights into successful blockchain adoption in FinTech, offering a roadmap for industry stakeholders to leverage this technology for enhanced efficiency, security, and innovation in financial services.

DECENTRALIZED VS. CENTRALIZED DATABASE SOLUTIONS IN BLOCKCHAIN: ADVANTAGES, CHALLENGES, AND USE CASES

his study provides a comprehensive examination of decentralized and centralized database solutions within the realm of blockchain technology, exploring the inherent strengths and weaknesses of each approach and their implications for various industries. Decentralized databases, characterized by distributed ledger technology, offer robust security and transparency by eliminating the need for a central authority, thereby reducing the risk of data tampering and fostering trust among participants. However, these benefits come with significant trade-offs, particularly in terms of scalability and performance, as the consensus mechanisms required in decentralized systems often result in slower transaction processing and higher resource consumption. In contrast, centralized databases, typically used in private or permissioned blockchains, excel in operational efficiency and scalability, enabling faster transaction processing and more streamlined management due to the presence of a central authority. Nevertheless, centralized systems introduce vulnerabilities, such as single points of failure and reduced transparency, which can undermine trust and compromise data integrity. The study also highlights industry-specific preferences, with sectors like healthcare and public governance leaning towards decentralized solutions for their emphasis on data integrity, while industries such as finance and logistics favor centralized systems for their superior performance and low latency. Moreover, the research identifies a critical gap in the literature regarding hybrid database models that could potentially integrate the strengths of both decentralized and centralized systems, offering a balanced approach that mitigates their respective weaknesses. These findings underscore the necessity for a tailored approach to database selection in blockchain implementations, aligned with the specific needs and goals of different industries, and suggest that further exploration of hybrid models could lead to more effective and adaptable blockchain solutions in the future.