Approaches of Blockchain with AI: Challenges & Future Direction
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Blockchain provides a distributed ledger for vulnerable components.
“On the other Blockchain is a provider of distributed ledger for any vulnerable components [241].”
From Federated learning-based AI approaches in smart healthcare: Concepts, taxonomies, challenges and open issues (2023) · cites this paper as [241]
Cited by
Sorted by citations
Rahman, A., Hossain, M. S., Muhammad, G., Kundu, D., Debnath, T., Rahman, M., Khan, M. S. I., Tiwari, P., & Band, S. S. (2023) · Cluster Computing · doi:10.1007/s10586-022-03658-4 · Cited by 399 · see citing works
Toward a greener future: A survey on sustainable blockchain applications and impact
Rani, P., Sharma, P., & Gupta, I. (2024) · Journal of Environmental Management · doi:10.1016/j.jenvman.2024.120273 · Cited by 81 · see citing works
Decentralizing construction AI applications using blockchain technology
Adel, K., Elhakeem, A., & Marzouk, M. M. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.116548 · Cited by 59 · see citing works
Anthony, B. (2024) · Cities · doi:10.1016/j.cities.2024.105198 · Cited by 33 · see citing works
A Hybrid Architecture combining Artificial intelligence and Blockchain for IoT Applications
Sivaganesan, D. (2021) · IRO Journal on Sustainable Wireless Systems · doi:10.36548/jsws.2020.3.006 · Cited by 13 · see citing works
“In [10] different IoT categories have been proposed and how they can be used to create a large set of data.”
BackgroundEvaluation of Block-Chain Transaction Accuracy using Neural Network Model
Veeraiah, V., Suthar, V., Reddy, A. Y., et al. (2022) · International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · doi:10.1109/icacite53722.2022.9823465 · Cited by 5 · see citing works
Integral Role of Blockchain and Artificial Intelligence in Sustainable Economic Development
Pandey, A., & Joseph, J. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-8664-4.ch012 · Cited by 5 · see citing works
Emergent Technologies for Supply Chain Risk and Disruption Management
Tripathi, P. K., Deshmukh, A. K., & Nath, T. (2023) · Flexible systems management · doi:10.1007/978-981-99-2629-9_4 · Cited by 5 · see citing works
Verification of Smart Contract Code Generated by Applying Artificial Intelligence
Peschanenko, V., Poltoratskyi, M., & Konnova, O. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-81372-6_1 · Cited by 2 · see citing works
Investigating the Role of Artificial Intelligence in Building Smart Contact on Block-Chain
Shukla, K. A., & Lodha, N. (2022) · International Conference on Emerging Smart Computing and Informatics (ESCI) · doi:10.1109/esci53509.2022.9758234 · Cited by 1 · see citing works
Evaluation of Block-chain Transaction Accuracy using Neural Network Model
Nassa, V. K., Varun, V. L., Chandra, A. S., et al. (2022) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i56241.2022.10072577
Retracted
- Authors
- Gulati, P., Sharma, A., Bhasin, K., & Azad, C.
- Affiliations
- National Institute of Technology Jamshedpur (IN)
- Corresponding author
- Gulati, Prerna
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2020
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W3163449779
- Cited by
- 11
- References
- 0
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 1 · 2022: 5 · 2021: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- blockchain, artificial intelligence, AI-blockchain integration, distributed ledger technology, cryptocurrency, smart contracts, blockchain architecture, data immutability, transparency, security (computing)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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