Blockchain-Based Research Data Sharing Framework for Incentivizing the Data Owners

Shrestha, Ajay Kumar; Vassileva, Julita

doi:10.1007/978-3-319-94478-4_19

Cited by 46 publications

(37 citation statements)

References 10 publications

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“…In [15], the authors mentioned some of the technical challenges present in the proposals adopting blockchain as part of their solutions. We proposed [2] a usable blockchain-based model for data sharing in the scientific research domain which addresses these challenges. Two different blockchains are used, providing accountability of access and incentives for sharing, maintaining the complete and updated information, and a verifiable record of the provenance, including all accesses/sharing/usages of the data.…”

Section: A Blockchain-based Research Data Sharing Systemmentioning

confidence: 99%

“…Two different blockchains are used, providing accountability of access and incentives for sharing, maintaining the complete and updated information, and a verifiable record of the provenance, including all accesses/sharing/usages of the data. This model is the basis for the user-acceptance study that we present in this paper, but since the technical detail is not essential for the study, the interested reader is referred to [2] for a full description.…”

Section: A Blockchain-based Research Data Sharing Systemmentioning

confidence: 99%

“…A flexible mechanism for obtaining and renewing consent for data use and sharing is required that provides appropriate and meaningful incentives to capitalize from data sharing and ensures transparency for users to be aware of which of their data has been accessed, by whom, for what purpose and under what conditions. Currently, blockchain technology and smart contracts have evolved as a promising means to support immutable and trusted in various use fields including research community [2], healthcare [3], agricultural [4], tourism domains [5] etc. Initially, blockchain was used only to implement virtual currencies [6], but the applications of the blockchain technology have since quickly evolved to a wide variety of use cases [7].…”

Section: Introductionmentioning

confidence: 99%

“…To bridge this gap and advance research in blockchains-and smart contracts-based systems, we adopted the extended Technology Acceptance Model (TAM) to examine the indicators that affect the user's acceptance of the system. We based our study on user evaluation of a prototype of a blockchain-based research datasharing framework [2] with the TAM validated tool deployed as a research instrument to collect data from 20 participants. We chose to investigate the influence of the perceived ease of use, perceived usefulness, perceived enjoyment and quality of the system, on the participants' intention to use the system.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

User Acceptance of Usable Blockchain-Based Research Data Sharing System: An Extended TAM-Based Study

Shrestha

Vassileva

2019

2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

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Blockchain technology has evolved as a promising means to transform data management models in many domains including healthcare, agricultural research, tourism domains etc. In the research community, a usable blockchain-based system can allow users to create a proof of ownership and provenance of the research work, share research data without losing control and ownership of it, provide incentives for sharing and give users full transparency and control over who access their data, when and for what purpose. The initial adoption of such blockchain-based systems is necessary for continued use of the services, but their user acceptance behavioral model has not been well investigated in the literature. In this paper, we take the Technology Acceptance Model (TAM) as a foundation and extend the external constructs to uncover how the perceived ease of use, perceived usability, quality of the system and perceived enjoyment influence the intention to use the blockchain-based system. We based our study on user evaluation of a prototype of a blockchain-based research data sharing framework using a TAM validated questionnaire. Our results show that, overall, all the individual constructs of the behavior model significantly influence the intention to use the system while their collective effect is found to be insignificant. The quality of the system and the perceived enjoyment have stronger influence on the perceived usefulness. However, the effect of perceived ease of use on the perceived usefulness is not supported. Finally, we discuss the implications of our findings. Keywords-TAM, behavior model, blockchain, smart contract, data sharing, privacy, perceived ease of use, perceived usefulness, quality of system, perceived enjoyment, behavioral Intention

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Section: A Blockchain-based Research Data Sharing Systemmentioning

confidence: 99%

Section: A Blockchain-based Research Data Sharing Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

User Acceptance of Usable Blockchain-Based Research Data Sharing System: An Extended TAM-Based Study

Shrestha

Vassileva

2019

2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

Self Cite

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“…Usually, the nodes are incentivized with mining rewards for taking part in the transaction validation activities, such as bitcoin/ Ethereum miners. Additionally, there are some proposals for using blockchain incorporating access control measures to ensure the privacy of data while sharing off-chain files [16], [17]. User modeling can benefit from a platform using distributed ledgers and smart contracts to ensure user-controlled privacy and data-sharing policies encoded in smart contracts.…”

Section: A Distributed Ledger Technologiesmentioning

confidence: 99%

User Data Sharing Frameworks: A Blockchain-Based Incentive Solution

Shrestha

Vassileva

2019

2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

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Currently, there is no universal method to track who shared what, with whom, when and for what purposes in a verifiable way to create an individual incentive for data owners. A platform that allows data owners to control, delete, and get rewards from sharing their data would be an important enabler of user data-sharing. We propose a usable blockchain-and smart contracts-based framework that allows users to store research data locally and share without losing control and ownership of it. We have created smart contracts for building automatic verification of the conditions for data access that also naturally supports building up a verifiable record of the provenance, incentives for users to share their data and accountability of access. The paper presents a review of the existing work of research data sharing, the proposed blockchain-based framework and an evaluation of the framework by measuring the transaction cost for smart contracts deployment. The results show that nodes responded quickly in all tested cases with a befitting transaction cost.

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Secure and efficient parameters aggregation protocol for federated incremental learning and its applications

Wang

Liang

Koe

et al. 2021

Int J of Intelligent Sys

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Federated Learning (FL) enables the deployment of distributed machine learning models over the cloud and Edge Devices (EDs) while preserving the privacy of sensitive local data, such as electronic health records. However, despite FL advantages regarding security and flexibility, current constructions still suffer from some limitations. Namely, heavy computation overhead on limited resources EDs, communication overhead in uploading converged local models' parameters to a centralized server for parameters aggregation, and lack of guaranteeing the acquired knowledge preservation in the face of incremental learning over new local data sets. This paper introduces a secure and resourcefriendly protocol for parameters aggregation in federated incremental learning and its applications. In this study, the central server relies on a new method for parameters aggregation called orthogonal gradient aggregation. Such a method assumes constant changes of each local data set and allows updating parameters in the orthogonal direction of previous parameters spaces.As a result, our new construction is robust against catastrophic forgetting, maintains the federated neural network accuracy, and is efficient in computation and

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Blockchain-Based Research Data Sharing Framework for Incentivizing the Data Owners

Cited by 46 publications

References 10 publications

User Acceptance of Usable Blockchain-Based Research Data Sharing System: An Extended TAM-Based Study

User Acceptance of Usable Blockchain-Based Research Data Sharing System: An Extended TAM-Based Study

User Data Sharing Frameworks: A Blockchain-Based Incentive Solution

Secure and efficient parameters aggregation protocol for federated incremental learning and its applications

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