Abstract
The relevance of data fusion in handling big data in blockchain-enabled healthcare systems is of utmost importance in today's data-driven healthcare landscape. As healthcare systems continue to generate vast amounts of data from various sources, the need to effectively manage and analyze this data becomes crucial for informed decision-making, improved patient outcomes, and efficient healthcare operations. The gaps for time complexity and inaccuracy of feature fusion in the existing algorithms have been identified by surveying the existing literature and this article is proposing a multi-attribute feature fusion algorithm blockchain communications based on ant colony neural networks (ACNN) to overcome the problems in the state-of-the-arts. This article applies the feature decomposition method for communication between blockchain-based healthcare transactions, and optimizes the information based on the data characteristics. The proposed algorithm identifies the properties and attributes of the data by making use of rough set theory. A genetic algorithm is also used to improve the ACNN which enhances the search ability by minimizing the space complexity of the solution space. The multi-attribute fusion mechanism extracts the information from the blockchain transactions and filters out the characteristics of data using the proposed method, and achieves better accuracy. The empirical results show that the fusion error of the blockchain communications based on multi-attribute feature fusion algorithm is relatively small and stable. The outcomes of the proposed fusion mechanism are promising and it has been found that the proposed mechanism produces accurate results with minimal errors. The average energy consumption rate during the transition of data is below 2% which reflects the viability of the proposed fusion mechanism for blockchain-based healthcare transactions.
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References
Drozdowski P, Stockhardt F, Rathgeb C et al (2021) Feature fusion methods for indexing and retrieval of biometric data: application to face recognition with privacy protection. IEEE Access 9:139361–139378
Kaur M (2023) AI- and IoT-based energy saving mechanism by minimizing hop delay in multi-hop and advanced optical system based optical channels. Opt Quant Electron 55:635
Kaur M, Khedkar G, Sakhare S et al (2023) A research study on the cervical cerclage to deal with cervical insufficiency using machine learning. Soft Comp. https://doi.org/10.1007/s00500-023-08622-x
Kim WT, Song J, Kim C (2020) A secure smart contract-based escrow scheme for cryptocurrency transactions. IEEE Access 8:96532–96545
Lan X et al.(2023) Multilevel feature fusion for end-to-end blind image quality assessment. In: IEEE Transactions on Broadcasting, https://doi.org/10.1109/TBC.2023.3262163.
Li J, Zhang Y, Chen X (2022b) Blockchain-based secure data sharing in healthcare systems. IEEE Access 10:1592–1602
Li Y, Liu L, Qin H et al. (2022a) Adaptive Deep Feature Fusion for Continuous Authentication with Data Augmentation. In: IEEE Transactions on Mobile Computing, https://doi.org/10.1109/TMC.2022.3186614.
Liu Y, Du X (2018) Blockchain and internet of things: a mutual boost for future information infrastructure. IEEE Comm Mag 56(9):145–151
Liu J, Xie Q, Zhang X et al (2021) A secure and efficient E-voting scheme based on blockchain and homomorphic encryption. IEEE Trans Ind Inform 17(3):2063–2073
Liu Y, Jiang X, Zhang Y (2022) A blockchain-based framework for secure and efficient supply chain management. IEEE Trans on Ind Inform 18(1):366–377
Lu S, Ding Y, Liu M et al (2023) Multiscale feature extraction and fusion of image and text in VQA. Int J Comput Intell Syst 16:54. https://doi.org/10.1007/s44196-023-00233-6
Nakamoto S (2019) Bitcoin: A Peer-to-Peer Electronic Cash System. Ledger 4:10–21
Noman AHM, Rafique MY (2020) Blockchain-based decentralized authentication for internet of things: a systematic review and future research directions. IEEE Access 8:111756–111778
Ren J, Jiang F, Huang Y et al (2021) A scalable and secure blockchain-based online auction system. IEEE Access 9:43418–43427
Song Y, Zhang X, Zhang W (2020) A new consensus mechanism for blockchain-based cryptocurrency. J of Comp Sc and Tech 35(1):109–124
Sujitha SS, Uma RN (2020) Blockchain for supply chain management and cryptocurrency. IEEE Transactions on Computational Social Systems 7(2):318–325
Sundarrajan K, Rajendran B (2023) Explainable efficient and optimized feature fusion network for surface defect detection. Int J Adv Manuf Technol. https://doi.org/10.1007/s00170-023-11789-0
Tran L-T, Ali MS, Bae S-H (2021) A feature fusion based indicator for training-free neural architecture search. IEEE Access 9:133914–133923
Walia S, Kumar K, Kumar M et al (2021) Fusion of handcrafted and deep features for forgery detection in digital images. IEEE Access 9:99742–99755. https://doi.org/10.1109/ACCESS.2021.3096240
Wang S, Xue X (2018) Blockchain for distributed systems security: a survey. IEEE Access 6:49782–49799
Wang S, Zhang J, Li K (2018) Blockchain-based trust management for public clouds. Future Gen Comp Sys 88:130–142
Wang C, Zhang C, Chen X et al (2021) A blockchain-based secure data sharing scheme for mobile edge computing. J of Net and Comp App 181:102909
Yu M, Kim H, Kim K (2022) Blockchain-based authentication and access control for edge computing. IEEE Trans on Cloud Comp 10(1):140–152
Zhang W, Kaur M (2022) A Novel QACS automatic extraction algorithm for extracting information in blockchain-based systems. IETE J of Research. https://doi.org/10.1080/03772063.2022.2030252
Zhang H, Li Z, Wei W et al (2021a) A blockchain-based framework for secure and efficient iot data sharing. IEEE Int of Things J 8(3):1887–1898
Zhang H, Luo X, Wang Z et al (2021b) A decentralized incentive mechanism for crowdsourcing based on blockchain. Future Gen Comp Sys 119:213–223
Zhang Y, Yang C, Liu X (2022a) A blockchain-based approach for secure and efficient data sharing in smart grid. IEEE Trans on Smart Grid 13(1):146–155
Zhang R, Zhang J, Zhang H (2022b) A novel blockchain-based IoT data sharing scheme with privacy preservation. IEEE Internet of Things J 9(1):410–421
Zhou M, Wang P (2021) Application of cloud computing and information fusion technology in green investment evaluation system. J Sens 2021:2292267
Zohar D (2018) Bitcoin: under the hood. Comm ACM 61(9):104–113
Funding
The work is supported by the Sichuan Science and Technology Project (No: 2019YJ0646); Chengdu Science and Technology Project (No: 2019-YF05-00224-SN); and Research Platform Foundation of Chengdu Polytechnic (No: 19KYPT01, No: 20KYTD07).
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Li, Y., Tan, Z., Yang, S. et al. Multi-attribute feature fusion algorithm for blockchain communications in healthcare systems using machine intelligence. Soft Comput 27, 17435–17445 (2023). https://doi.org/10.1007/s00500-023-09192-8
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DOI: https://doi.org/10.1007/s00500-023-09192-8