An integrated blockchain-enabled multi-channel vaccine supply chain network under hybrid uncertainties.

The recent pandemic caused by COVID-19 is considered an unparalleled disaster in history. Developing a vaccine distribution network can provide valuable support to supply chain managers. Prioritizing the assigned available vaccines is crucial due to the limited supply at the final stage of the vaccine supply chain. In addition, parameter uncertainty is a common occurrence in a real supply chain, and it is essential to address this uncertainty in planning models. On the other hand, blockchain technology, being at the forefront of technological advancements, has the potential to enhance transparency within supply chains. Hence, in this study, we develop a new mathematical model for designing a COVID-19 vaccine supply chain network. In this regard, a multi-channel network model is designed to minimize total cost and maximize transparency with blockchain technology consideration. This addresses the uncertainty in supply, and a scenario-based multi-stage stochastic programming method is presented to handle the inherent uncertainty in multi-period planning horizons. In addition, fuzzy programming is used to face the uncertain price and quality of vaccines. Vaccine assignment is based on two main policies including age and population-based priority. The proposed model and method are validated and tested using a real-world case study of Iran. The optimum design of the COVID-19 vaccine supply chain is determined, and some comprehensive sensitivity analyses are conducted on the proposed model. Generally, results demonstrate that the multi-stage stochastic programming model meaningfully reduces the objective function value compared to the competitor model. Also, the results show that one of the efficient factors in increasing satisfied demand and decreasing shortage is the price of each type of vaccine and its agreement.

Taxonomic insights into ethereum smart contracts by linking application categories to security vulnerabilities.

The expansion of smart contracts on the Ethereum blockchain has created a diverse ecosystem of decentralized applications. This growth, however, poses challenges in classifying and securing these contracts. Existing research often separately addresses either classification or vulnerability detection, without a comprehensive analysis of how contract types are related to security risks. Our study addresses this gap by developing a taxonomy of smart contracts and examining the potential vulnerabilities associated with each category. We use the Latent Dirichlet Allocation (LDA) model to analyze a dataset of over 100,040 Ethereum smart contracts, which is notably larger than those used in previous studies. Our analysis categorizes these contracts into eleven groups, with five primary categories: Notary, Token, Game, Financial, and Blockchain interaction. This categorization sheds light on the various functions and applications of smart contracts in today's blockchain environment. In response to the growing need for better security in smart contract development, we also investigate the link between these categories and common vulnerabilities. Our results identify specific vulnerabilities associated with different contract types, providing valuable insights for developers and auditors. This relationship between contract categories and vulnerabilities is a new contribution to the field, as it has not been thoroughly explored in previous research. Our findings offer a detailed taxonomy of smart contracts and practical recommendations for enhancing security. By understanding how contract categories correlate with vulnerabilities, developers can implement more effective security measures, and auditors can better prioritize their reviews. This study advances both academic knowledge of smart contracts and practical strategies for securing decentralized applications on the Ethereum platform.

Privacy preserving technology in ophthalmology.

PURPOSE OF REVIEW: Patient privacy protection is a critical focus in medical practice. Advances over the past decade in big data have led to the digitization of medical records, making medical data increasingly accessible through frequent data sharing and online communication. Periocular features, iris, and fundus images all contain biometric characteristics of patients, making privacy protection in ophthalmology particularly important. Consequently, privacy-preserving technologies have emerged, and are reviewed in this study. RECENT FINDINGS: Recent findings indicate that general medical privacy-preserving technologies, such as federated learning and blockchain, have been gradually applied in ophthalmology. However, the exploration of privacy protection techniques of specific ophthalmic examinations, like digital mask, is still limited. Moreover, we have observed advancements in addressing ophthalmic ethical issues related to privacy protection in the era of big data, such as algorithm fairness and explainability. SUMMARY: Future privacy protection for ophthalmic patients still faces challenges and requires improved strategies. Progress in privacy protection technology for ophthalmology will continue to promote a better healthcare environment and patient experience, as well as more effective data sharing and scientific research.

A robust algorithm for authenticated health data access via blockchain and cloud computing.

In modern healthcare, providers increasingly use cloud services to store and share electronic medical records. However, traditional cloud hosting, which depends on intermediaries, poses risks to privacy and security, including inadequate control over access, data auditing, and tracking data origins. Additionally, current schemes face significant limitations such as scalability concerns, high computational overhead, practical implementation challenges, and issues with interoperability and data standardization. Unauthorized data access by cloud providers further exacerbates these concerns. Blockchain technology, known for its secure and decentralized nature, offers a solution by enabling secure data auditing in sharing systems. This research integrates blockchain into healthcare for efficient record management. We proposed a blockchain-based method for secure EHR management and integrated Ciphertext-Policy Attribute-Based Encryption (CP-ABE) for fine-grained access control. The proposed algorithm combines blockchain and smart contracts with a cloud-based healthcare Service Management System (SMS) to ensure secure and accessible EHRs. Smart contracts automate key management, encryption, and decryption processes, enhancing data security and integrity. The blockchain ledger authenticates data transactions, while the cloud provides scalability. The SMS manages access requests, enhancing resource allocation and response times. A dual authentication system confirms patient keys before granting data access, with failed attempts leading to access revocation and incident logging. Our analyses show that this algorithm significantly improves the security and efficiency of health data exchanges. By combining blockchain's decentralized structure with the cloud's scalability, this approach significantly improves EHR security protocols in modern healthcare setting.

Blockchain implementation for food safety in supply chain: A review.

Food safety has emerged as the topmost priority in the current fast-paced food industry era. According to the World Health Organization, around 600 million people, approximately 1 in 10 individuals worldwide, experience illness due to contaminated food consumption, resulting in nearly 0.42 million fatalities annually. The recent development in software and hardware sectors has created opportunities to improve the safety concerns in the food supply chain. The objective of this review is to explain the fundamentals of blockchain and its integration into the supply chain of various food commodities to enhance food safety. This paper presents the analysis of 31 conceptual works, 10 implementation works, 39 case studies, and other investigations in blockchain-based food supply chain from a total of 80 published papers. In this paper, the significance of adapting conceptual ideas into practical applications for effectively tracing food commodities throughout the supply chain has been discussed. This paper also describes the transformative role of blockchain platforms in the food industry, providing a decentralized and transparent ledger to access real-time and immutable records of a product's journey. In addition, both the positive impacts and challenges associated with implementing blockchain technology in the food supply chain have been evaluated. In summary, the blockchain-based food supply chains offer greater transparency, traceability, and trust, ultimately resulting in higher standards of food safety and quality.

PatCen: A blockchain-based patient-centric mechanism for the granular access control of infectious disease-related test records.

The recent global outbreaks of infectious diseases such as COVID-19, yellow fever, and Ebola have highlighted the critical need for robust health data management systems that can rapidly adapt to and mitigate public health emergencies. In contrast to traditional systems, this study introduces an innovative blockchain-based Electronic Health Record (EHR) access control mechanism that effectively safeguards patient data integrity and privacy. The proposed approach uniquely integrates granular data access control mechanism within a blockchain framework, ensuring that patient data is only accessible to explicitly authorized users and thereby enhancing patient consent and privacy. This system addresses key challenges in healthcare data management, including preventing unauthorized access and overcoming the inefficiencies inherent in traditional access mechanisms. Since the latency is a sensitive factor in healthcare data management, the simulations of the proposed model reveal substantial improvements over existing benchmarks in terms of reduced computing overhead, increased throughput, minimized latency, and strengthened overall security. By demonstrating these advantages, the study contributes significantly to the evolution of health data management, offering a scalable, secure solution that prioritizes patient autonomy and privacy in an increasingly digital healthcare landscape.

A cross domain access control model for medical consortium based on DBSCAN and penalty function.

BACKGROUND: Graded diagnosis and treatment, referral, and expert consultations between medical institutions all require cross domain access to patient medical information to support doctors' treatment decisions, leading to an increase in cross domain access among various medical institutions within the medical consortium. However, patient medical information is sensitive and private, and it is essential to control doctors' cross domain access to reduce the risk of leakage. Access control is a continuous and long-term process, and it first requires verification of the legitimacy of user identities, while utilizing control policies for selection and management. After verifying user identity and access permissions, it is also necessary to monitor unauthorized operations. Therefore, the content of access control includes authentication, implementation of control policies, and security auditing. Unlike the existing focus on authentication and control strategy implementation in access control, this article focuses on the control based on access log security auditing for doctors who have obtained authorization to access medical resources. This paper designs a blockchain based doctor intelligent cross domain access log recording system, which is used to record, query and analyze the cross domain access behavior of doctors after authorization. Through DBSCAN clustering analysis of doctors' cross domain access logs, we find the abnormal phenomenon of cross domain access, and build a penalty function to dynamically control doctors' cross domain access process, so as to reduce the risk of Data breach. Finally, through comparative analysis and experiments, it is shown that the proposed cross domain access control model for medical consortia based on DBSCAN and penalty function has good control effect on the cross domain access behavior of doctors in various medical institutions of the medical consortia, and has certain feasibility for the cross domain access control of doctors.

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.

DRPChain: A new blockchain-based trusted DRM scheme for image content protection.

The unauthorized replication and distribution of digital images pose significant challenges to copyright protection. While existing solutions incorporate blockchain-based techniques such as perceptual hashing and digital watermarking, they lack large-scale experimental validation and a dedicated blockchain consensus protocol for image copyright management. This paper introduces DRPChain, a novel digital image copyright management system that addresses these issues. DRPChain employs an efficient cropping-resistant robust image hashing algorithm to defend against 14 common image attacks, demonstrating an 85% success rate in watermark extraction, 10% higher than the original scheme. Moreover, the paper designs the K-Raft consensus algorithm tailored for image copyright protection. Comparative experiments with Raft and benchmarking against PoW and PBFT algorithms show that K-Raft reduces block error rates by 2%, improves efficiency by 300ms compared to Raft, and exhibits superior efficiency,decentralization, and throughput compared to PoW and PBFT. These advantages make K-Raft more suitable for digital image copyright protection. This research contributes valuable insights into using blockchain technology for digital copyright protection, providing a solid foundation for future exploration.

An efficient blockchain-based authentication scheme with transferability.

In the development of web applications, the rapid advancement of Internet technologies has brought unprecedented opportunities and increased the demand for user authentication schemes. Before the emergence of blockchain technology, establishing trust between two unfamiliar entities relied on a trusted third party for identity verification. However, the failure or malicious behavior of such a trusted third party could undermine such authentication schemes (e.g., single points of failure, credential leaks). A secure authorization system is another requirement of user authentication schemes, as users must authorize other entities to act on their behalf in some situations. If the transfer of authentication permissions is not adequately restricted, security risks such as unauthorized transfer of permissions to entities may occur. Some research has proposed blockchain-based decentralized user authentication solutions to address these risks and enhance availability and auditability. However, as we know, most proposed schemes that allow users to transfer authentication permissions to other entities require significant gas consumption when deployed and triggered in smart contracts. To address this issue, we proposed an authentication scheme with transferability solely based on hash functions. By combining one-time passwords with Hashcash, the scheme can limit the number of times permissions can be transferred while ensuring security. Furthermore, due to its reliance solely on hash functions, our proposed authentication scheme has an absolute advantage regarding computational complexity and gas consumption in smart contracts. Additionally, we have deployed smart contracts on the Goerli test network and demonstrated the practicality and efficiency of this authentication scheme.

Designing A Blockchain-Empowered Telehealth Artifact for Decentralized Identity Management and Trustworthy Communication: Interdisciplinary Approach.

BACKGROUND: Telehealth played a critical role during the COVID-19 pandemic and continues to function as an essential component of health care. Existing platforms cannot ensure privacy and prevent cyberattacks. OBJECTIVE: The main objectives of this study are to understand existing cybersecurity issues in identity management and trustworthy communication processes in telehealth platforms and to design a software architecture integrated with blockchain to improve security and trustworthiness with acceptable performance. METHODS: We improved personal information security in existing telehealth platforms by adopting an innovative interdisciplinary approach combining design science, social science, and computer science in the health care domain, with prototype implementation. We used the design science research methodology to implement our overall design. We innovated over existing telehealth platforms with blockchain integration that improves health care delivery services in terms of security, privacy, and efficiency. We adopted a user-centric design approach and started with user requirement collection, followed by system functionality development. Overall system implementation facilitates user requirements, thus promoting user behavior for the adoption of the telehealth platform with decentralized identity management and an access control mechanism. RESULTS: Our investigation identified key challenges to identity management and trustworthy communication processes in telehealth platforms used in the current health care domain. By adopting distributed ledger technology, we proposed a decentralized telehealth platform to support identity management and a trustworthy communication process. Our design and prototype implementation using a smart contract-driven telehealth platform to provide decentralized identity management and trustworthy communication with token-based access control addressed several security challenges. This was substantiated by testing with 10,000 simulated transactions across 5 peers in the Rahasak blockchain network. The proposed design provides resistance to common attacks while maintaining a linear time overhead, demonstrating improved security and efficiency in telehealth services. We evaluated the performance in terms of transaction throughput, smart contract execution time, and block generation time. To create a block with 10,000 transactions, it takes 8 seconds on average, which is an acceptable overhead for blockchain-based applications. CONCLUSIONS: We identified technical limitations in current telehealth platforms. We presented several design innovations using blockchain to prototype a system. We also presented the implementation details of a unique distributed architecture for a trustworthy communication system. We illustrated how this design can overcome privacy, security, and scalability limitations. Moreover, we illustrated how improving these factors sets the stage for improving and standardizing the application and for the wide adoption of blockchain-enabled telehealth platforms.

Non-Fungible Tokens (NFTs) in Healthcare: A Systematic Review.

Amid global health challenges, resilient health systems require continuous innovation and progress. Stakeholders highlight the critical role of digital technologies in accelerating this progress. However, the digital health field faces significant challenges, including the sensitivity of health data, the absence of evidence-based standards, data governance issues, and a lack of evidence on the impact of digital health strategies. Overcoming these challenges is crucial to unlocking the full potential of digital health innovations in enhancing healthcare delivery and outcomes. Prioritizing security and privacy is essential in developing digital health solutions that are transparent, accessible, and effective. Non-fungible tokens (NFTs) have gained widespread attention, including in healthcare, offering innovative solutions and addressing challenges through blockchain technology. This paper addresses the gap in systematic-level studies on NFT applications in healthcare, aiming to comprehensively analyze use cases and associated research challenges. The search included primary studies published between 2014 and November 2023, searching in a balanced set of databases compiling articles from different fields. A review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework and strictly focusing on research articles related to NFT applications in the healthcare sector. The electronic search retrieved 1902 articles, ultimately resulting in 15 articles for data extraction. These articles span applications of NFTs in medical devices, pathology exams, diagnosis, pharmaceuticals, and other healthcare domains, highlighting their potential to eliminate centralized trust sources in health informatics. The review emphasizes the adaptability and versatility of NFT-based solutions, indicating their broader applicability across various healthcare stages and expansion into diverse industries. Given their role in addressing challenges associated with enhancing data integrity, availability, non-repudiation, and authentication, NFTs remain a promising avenue for future research within digital health solutions.

The role of blockchain to secure internet of medical things.

This study explores integrating blockchain technology into the Internet of Medical Things (IoMT) to address security and privacy challenges. Blockchain's transparency, confidentiality, and decentralization offer significant potential benefits in the healthcare domain. The research examines various blockchain components, layers, and protocols, highlighting their role in IoMT. It also explores IoMT applications, security challenges, and methods for integrating blockchain to enhance security. Blockchain integration can be vital in securing and managing this data while preserving patient privacy. It also opens up new possibilities in healthcare, medical research, and data management. The results provide a practical approach to handling a large amount of data from IoMT devices. This strategy makes effective use of data resource fragmentation and encryption techniques. It is essential to have well-defined standards and norms, especially in the healthcare sector, where upholding safety and protecting the confidentiality of information are critical. These results illustrate that it is essential to follow standards like HIPAA, and blockchain technology can help ensure these criteria are met. Furthermore, the study explores the potential benefits of blockchain technology for enhancing inter-system communication in the healthcare industry while maintaining patient privacy protection. The results highlight the effectiveness of blockchain's consistency and cryptographic techniques in combining identity management and healthcare data protection, protecting patient privacy and data integrity. Blockchain is an unchangeable distributed ledger system. In short, the paper provides important insights into how blockchain technology may transform the healthcare industry by effectively addressing significant challenges and generating legal, safe, and interoperable solutions. Researchers, doctors, and graduate students are the audience for our paper.

Blockchain-based proxy re-encryption access control method for biological risk privacy protection of agricultural products.

In today's globalized agricultural system, information leakage of agricultural biological risk factors can lead to business risks and public panic, jeopardizing corporate reputation. To solve the above problems, this study constructs a blockchain network for agricultural product biological risk traceability based on agricultural product biological risk factor data to achieve traceability of biological risk traceability data of agricultural product supply chain to meet the sustainability challenges. To guarantee the secure and flexible sharing of agricultural product biological risk privacy information and limit the scope of privacy information dissemination, the blockchain-based proxy re-encryption access control method (BBPR-AC) is designed. Aiming at the problems of proxy re-encryption technology, such as the third-party agent being prone to evil, the authorization judgment being cumbersome, and the authorization process not automated, we design the proxy re-encryption access control mechanism based on the traceability of agricultural products' biological risk factors. Designing an attribute-based access control (ABAC) mechanism based on the traceability blockchain for agricultural products involves defining the attributes of each link in the agricultural supply chain, formulating policies, and evaluating and executing these policies, deployed in the blockchain system in the form of smart contracts. This approach achieves decentralization of authorization and automation of authority judgment. By analyzing the data characteristics within the agricultural product supply chain to avoid the malicious behavior of third-party agents, the decentralized blockchain system acts as a trusted third-party agent, and the proxy re-encryption is combined with symmetric encryption to improve the encryption efficiency. This ensures a efficient encryption process, making the system safe, transparent, and efficient. Finally, a prototype blockchain system for traceability of agricultural biological risk factors is built based on Hyperledger Fabric to verify this research method's reliability, security, and efficiency. The experimental results show that this research scheme's initial encryption, re-encryption, and decryption sessions exhibit lower computational overheads than traditional encryption methods. When the number of policies and the number of requests in the access control session is 100, the policy query latency is less than 400 ms, the request-response latency is slightly more than 360ms, and the data uploading throughput is 48.7 tx/s. The data query throughput is 81.8 tx/s, the system performance consumption is low and can meet the biological risk privacy protection needs of the agricultural supply chain. The BBPR-AC method proposed in this study provides ideas for achieving refined traceability management in the agricultural supply chain and promoting digital transformation in the agricultural industry.

Distributed management of patient data-sharing informed consents for clinical research.

BACKGROUND: The consent protocol is now a critical part in the overall orchestration of clinical research. We aimed to demonstrate the feasibility of an Ethereum-based informed consent system, which includes an immutable and automated channel of consent matching, to simultaneously assure patient privacy and increase the efficiency of researchers' data access. METHOD: We simulated a multi-site scenario, each assigned 10000 consent records. A consent record contained one patient's data-sharing preference with regards to seven data categories. We developed a blockchain-based infrastructure with a smart contract to record consents on-chain, and to query consenting patients corresponding to specific criteria. We measured our system's recording efficiency against a baseline design and verified accuracy by testing an exhaustive list of possible queries. RESULTS: Our method achieved ∼3-4% lead with an average insertion speed of ∼2 s per record per node on either a 3-, 4- or 5-node network, and 100 % accuracy. It also outperformed other solutions in external validation. DISCUSSION: The speed we achieved is reasonable in a real-world system under the realistic assumption that patients may not change their minds too frequently, with the added benefit of immutability. Furthermore, the per-insertion time did improve slightly as the number of network nodes increased, attesting to the benefit of node parallelism as it suggests no attrition of insertion efficiency due to scale of nodes. CONCLUSIONS: Our work confirms the technical feasibility of a blockchain-based consent mechanism, assuring patients with an immutable audit trail, and providing researchers with an efficient way to reach their cohorts.

A scalable blockchain-enabled federated learning architecture for edge computing.

Various deep learning techniques, including blockchain-based approaches, have been explored to unlock the potential of edge data processing and resultant intelligence. However, existing studies often overlook the resource requirements of blockchain consensus processing in typical Internet of Things (IoT) edge network settings. This paper presents our FLCoin approach. Specifically, we propose a novel committee-based method for consensus processing in which committee members are elected via the FL process. Additionally, we employed a two-layer blockchain architecture for federated learning (FL) processing to facilitate the seamless integration of blockchain and FL techniques. Our analysis reveals that the communication overhead remains stable as the network size increases, ensuring the scalability of our blockchain-based FL system. To assess the performance of the proposed method, experiments were conducted using the MNIST dataset to train a standard five-layer CNN model. Our evaluation demonstrated the efficiency of FLCoin. With an increasing number of nodes participating in the model training, the consensus latency remained below 3 s, resulting in a low total training time. Notably, compared with a blockchain-based FL system utilizing PBFT as the consensus protocol, our approach achieved a 90% improvement in communication overhead and a 35% reduction in training time cost. Our approach ensures an efficient and scalable solution, enabling the integration of blockchain and FL into IoT edge networks. The proposed architecture provides a solid foundation for building intelligent IoT services.

The application of metaverse in healthcare.

While metaverse is widely discussed, comprehension of its intricacies remains limited to a select few. Conceptually akin to a three-dimensional embodiment of the Internet, the metaverse facilitates simultaneous existence in both physical and virtual domains. Fundamentally, it embodies a visually immersive virtual environment, striving for authenticity, where individuals engage in real-world activities such as commerce, gaming, social interaction, and leisure pursuits. The global pandemic has accelerated digital innovations across diverse sectors. Beyond strides in telehealth, payment systems, remote monitoring, and secure data exchange, substantial advancements have been achieved in artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and blockchain technologies. Nevertheless, the metaverse, in its nascent stage, continues to evolve, harboring significant potential for revolutionizing healthcare. Through integration with the Internet of Medical Devices, quantum computing, and robotics, the metaverse stands poised to redefine healthcare systems, offering enhancements in surgical precision and therapeutic modalities, thus promising profound transformations within the industry.

Federated Electronic Health Records Using a Blockchain.

The Valkyrie project aims to develop a demonstration Federated Electronic Health Record for the use of mental health practitioners in Norway. Information for the record is drawn from existing records in Source Systems operating across primary and secondary care. Recording of information in any such system, in response to a healthcare event, triggers the generation of an Encrypted Token, containing summary metadata about the event, clinical coding indicating its clinical context and a locator that can be used to retrieve the full record of the event from the original Source System. The Valkyrie architecture consists of a number of interlinked Security Domains, each with its own private and public keys, through which the Encrypted Tokens are passed. Each Security Domain performs a specific function on a set of Tokens and only has access to the information within each Token that is necessary to perform that function. This paper describes the structure of the Encrypted Token, the function of each Security Domain and the orchestration of the flow of Tokens through the Domains. Together this allows a user to run a Valkyrie Session, in which they can view the content of a patient record, where all content has been drawn in real-time from heterogenous Source Systems (ISO13606- and openEHR-based) and is destroyed when the session terminates.

Securing Reproducibility and Accountability in Distributed Healthcare Analytics: A Framework Based on Blockchain and Cryptography.

The results and details of the clinical studies and research must be securely stored to ensure reliability, accountability, and prevent malicious misuse. To accomplish this, a secure method for storing metadata and study results is crucial. Also, a mechanism to ensure accountability for both data owners and researchers is needed. In this way, data owners and the scientific community can rely on and verify results and methods presented by researchers, while researchers can check the validity of the analyzed data and have proof of authorship for their work. A modular framework is presented in this paper, which utilizes blockchain and cryptography to store study results and metadata, along with proof of accountability. The framework has been tested within a privacy-preserving distributed analytics infrastructure.