FGFL: A blockchain-based fair incentive governor for Federated Learning

Gao, Liang; Li, Li; Chen, Yingwen; Xu, Cheng‐Zhong

doi:10.1016/j.jpdc.2022.01.019

Cited by 41 publications

(15 citation statements)

References 45 publications

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“…To address this and establish a decentralized, publicly auditable federated learning ecosystem founded on trust and incentives, they recommend adopting blockchain technology. Similarly, the authors in [46] underscore the necessity of reasonable incentives, noting that without them, participants may hesitate to engage in the learning process. Moreover, the study emphasizes the pressing demand for incentive strategies to deter malicious participants aiming to degrade the model's performance.…”

Section: Blockchain-enabled Federated Learning (Bcfl)mentioning

confidence: 99%

Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification

Goh,

Kim,

Lee

et al. 2023

IEEE Access

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This paper presents a novel reference architecture for blockchain-enabled federated learning (BCFL), a state-of-the-art approach that amalgamates the strengths of federated learning and blockchain technology. We define smart contract functions, stakeholders and their roles, and the use of interplanetary file system (IPFS) as key components of BCFL and conduct a comprehensive analysis. In traditional centralized federated learning, the selection of local nodes and the collection of learning results for each round are merged under the control of a central server. In contrast, in BCFL, all these processes are monitored and managed via smart contracts. Additionally, we propose an extension architecture to support both crossdevice and cross-silo federated learning scenarios. Furthermore, we implement and verify the architecture in a practical real-world Ethereum development environment. Our BCFL reference architecture provides significant flexibility and extensibility, accommodating the integration of various additional elements, as per specific requirements and use cases, thereby rendering it an adaptable solution for a wide range of BCFL applications. As a prominent example of extensibility, decentralized identifiers (DIDs) have been employed as an authentication method to introduce practical utilization within BCFL. This study not only bridges a crucial gap between research and practical deployment but also lays a solid foundation for future explorations in the realm of BCFL. The pivotal contribution of this study is the successful implementation and verification of a realistic BCFL reference architecture. We intend to make the source code publicly accessible shortly, fostering further advancements and adaptations within the community.INDEX TERMS Blockchain, federated learning, blockchain-enabled federated learning (BCFL), reference architecture, Ethereum test network deployment, decentralized identifier (DID), client selection, client evaluation, smart contracts, data privacy and security.

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Section: Blockchain-enabled Federated Learning (Bcfl)mentioning

confidence: 99%

Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification

Goh,

Kim,

Lee

et al. 2023

IEEE Access

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“…Otherwise, workers may be reluctant to do the training and report useless or even harmful parameters to global model aggregators. In order to jointly satisfy the privacy, integrity, and fair incentives of blockchain-enabled federated learning, Rückel et al [157] proposed a federated learning framework that incentivizes each client based on their individual contribution to the global model, uses zero-knowledge proofs to ensure data integrity, and adopts local differential privacy to perturb each clients' model update with Laplacian noise to ensure the data privacy. Gao et al [158] proposed FGFL model that assesses workers based on both contribution and reputation.…”

Section: Incentive Mechanisms In Blockchain-enabled Flmentioning

confidence: 99%

Recent Advances of Blockchain and Its Applications

2022

J. Soc. Comput.

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Blockchain is an emerging decentralized data collection, sharing, and storage technology, which have provided abundant transparent, secure, tamper-proof, secure, and robust ledger services for various realworld use cases. Recent years have witnessed notable developments of blockchain technology itself as well as blockchain-enabled applications. Most existing surveys limit the scopes on several particular issues of blockchain or applications, which are hard to depict the general picture of current giant blockchain ecosystem.In this paper, we investigate recent advances of both blockchain technology and its most active research topics in real-world applications. We first review the recent developments of consensus and storage mechanisms and communication schema in general blockchain systems. Then extensive literature review is conducted on blockchain-enabled Internet of Things (IoT), edge computing, federated learning, and several emerging applications including healthcare, COVID-19 pandemic, online social network, and supply chain, where detailed specific research topics are discussed in each. Finally, we discuss the future directions, challenges, and opportunities in both academia and industry.

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“…FGFL [111], a novel incentive governor for FL that assesses workers' contributions and reputations to reward efficient workers fairly and eliminate malicious ones. FGFL contains two main parts: a fair incentive mechanism and a reliable incentive management system.…”

Section: ) Game Theory Based Trustworthy Incentive Mechanismmentioning

confidence: 99%

Common misconceptions regarding COVID-19 among health care professionals: an online global cross-sectional survey

Tariq¹,

Hamid²,

Mashood³

et al. 2020

J Oral Res

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Background: The COVID-19 pandemic has taken the world by storm, with cases continuously increasing by the hour and with a shortage of information regarding the virus available to the general public. Despite the availability of trusted online sources, there are still misconceptions relating to the virus floating around. This study aimed to find out the level of misconceptions among healthcare professionals (HCPs) worldwide about the ensuing COVID-19 pandemic. Materials and Methods: A descriptive cross sectional study was conducted through a global online survey. The self-administered questionnaire was designed and registered at an online website (Kwiksurveys). A total of 652 participants from 35 different countries across the world responded. Statistical analysis was performed using SPSS version 23. Socio-demographic and discipline characteristics were compared with the help of the chi-square test and univariate and multivariate logistic regression to find significant relationships. Results: Among all HCPs, general physicians (61.2%) were the most common respondents. The responses from females (63.3%) almost doubled those of men, and nearly half of the participants were working in private institutes (49.2%). Additionally, the major source of information used by HCPs about COVID-19 was social media (55.4%). Regarding misconception assessment, 71.6% of participants had correct concepts regarding COVID-19. However, 28.4% had incorrect information. Female HCPs were 1.49 times more likely to have correct concepts compared to males (OR=1.49, 95% CI=1.04-2.14). Conclusions: The majority of the HCPs were keeping themselves up-to-date with current information concerning the knowledge, prevention, and hygiene practices of COVID-19 infection. However, some misconceptions are deeply rooted in the mindsets of HCPs worldwide and need to be addressed by the continuous professional development of HCPs. The availability of reliable sources of information on the pandemic should be encouraged, with adequate explanations also available to the general public in simple terms.

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FGFL: A blockchain-based fair incentive governor for Federated Learning

Cited by 41 publications

References 45 publications

Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification

Blockchain-Enabled Federated Learning: A Reference Architecture Design, Implementation, and Verification

Recent Advances of Blockchain and Its Applications

Common misconceptions regarding COVID-19 among health care professionals: an online global cross-sectional survey

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