Intersection of AI and Blockchain Technology: Concerns and Prospects

Vikhyath, K B; Sanjana, R. K.; Vismitha, N. V.

doi:10.1007/978-3-030-84337-3_5

“…In Machine learning application such as lean and augmented data learning [35,46], hybrid learning models [36], un-supervised models [37,47], digital twins [38,49,50], and explainable AI [39,40] there are few emerging trends presented in Table 1.…”

Section: Blockchain Technologymentioning

confidence: 99%

“…-We provide an overview of blockchain fundamentals, major characteristics, and how these elements might be used in Deep Learning. [35,46] Lean and augmented data learning Enabling transfer learning between several Al applications to guarantee the high availability of appropriate and correct data Applications with less data availability Reliability, Provenance, and Trust [36,47] Hybrid Learning Models…”

Section: Blockchain Technologymentioning

confidence: 99%

WITHDRAWN: Integration of Blockchain Technology with Deep Learning Approaches: Vision and Future Opportunities

Afaq

¹

,

Manocha

²

2022

Preprint

0

2

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Recently, Deep Learning and blockchain technology has gained successful attention in recent research due to their high potential for generating accurate decision. The operational transparency, traceability, dependability, security, and trustworthy data provenance characteristics are offered by the vast majority of current deep learning approaches that are developed on centralized servers. Therefore, using centralized data to train Deep Learning models makes them vulnerable to the single point of failure issue. In this article, the benefits of combining Blockchain and Deep Learning algorithms are explored. Moreover, the state-of-the-art literature is reviewed to find out the most possible way to integrate these two technologies for an optimal solution. Based on the literature survey this article is divided by a thematic taxonomy that includes seven different parameters such as Deep Learning techniques, protocols, domains, types of blockchain, use of deep learning and blockchain, and datasets. We have outlined the advantages and disadvantages of the most advanced blockchain-based deep learning frameworks to give insightful discussions. At last, the most important challenges that need further research are also highlighted with future recommendations.

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“…In Machine learning application such as lean and augmented data learning [35,46], hybrid learning models [36], un-supervised models [37,47], digital twins [38,49,50], and explainable AI [39,40] there are few emerging trends…”

Section: Intelligent Approachesmentioning

confidence: 99%

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

Afaq

¹

,

Manocha

²

2022

Preprint

1

0

1

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A recent study has successfully focused on Deep Learning and Blockchain technologies because of their tremendous potential for producing reliable decisions. The bulk of contemporary deep learning techniques implemented on centralized servers gives operational transparency, traceability, reliability, security, and reliable data provenance qualities. Deep Learning models are therefore susceptible to the single point of failure problem since they are trained using centralized data. The advantages of merging Blockchain with Deep Learning algorithms are examined in this paper. Additionally, current research is examined to determine the best strategy to combine these two technologies for the best outcome.

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“…It ensures the data which is stored in the database is secure and properly controlled by the patient and accessed by the others as per the consent of the owner. Self-executing [35,46] Lean and augmented data learning Enabling transfer learning between several Al applications to guarantee the high availability of appropriate and correct data Applications with less data availability Reliability, Provenance, and Trust [36,47] Hybrid Learning Models…”

Section: Deep Learning (Dl)mentioning

confidence: 99%

WITHDRAWN: Integration of Blockchain Technology with Deep Learning Approaches: Vision and Future Opportunities

Afaq

¹

,

Manocha

²

2022

Preprint

0

View full text Add to dashboard Cite

A recent study has successfully focused on Deep Learning and Blockchain technologies because of their tremendous potential for producing reliable decisions. The bulk of contemporary deep learning techniques implemented on centralized servers gives operational transparency, traceability, reliability, security, and reliable data provenance qualities. Deep Learning models are therefore susceptible to the single point of failure problem since they are trained using centralized data. The advantages of merging Blockchain with Deep Learning algorithms are examined in this paper. Additionally, current research is examined to determine the best strategy to combine these two technologies for the best outcome.

show abstract

Intersection of AI and Blockchain Technology: Concerns and Prospects

Cited by 8 publications

References 16 publications

WITHDRAWN: Integration of Blockchain Technology with Deep Learning Approaches: Vision and Future Opportunities

WITHDRAWN: Integration of Blockchain Technology with Deep Learning Approaches: Vision and Future Opportunities

WITHDRAWN: Blockchain Technology with Deep Learning Adoptation for Various Applications: Vision and Future Opportunities

WITHDRAWN: Integration of Blockchain Technology with Deep Learning Approaches: Vision and Future Opportunities

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