Blockchain Based Cross Chain Trusted Clinical Records Sharing System
Keywords:Blockchain, Edge Computing, Clinical Records, Consensus Algorithm, Fabric Alliance Chain
The progress of clinical informatization depends greatly on the trustworthy exchange of electronic healthcare records, which are sensitive and important private data assets for patients. The longer access time, problematic cross-domain trustworthy exchange, and insecure storage of patient clinical record data are all discussed in this study. Designing a cross-chain trustworthy sharing solution for electronic clinical records based on the Fabric alliance chain required the use of blockchain and edge computing in this work. The system is separated into patient mobile applications, hospital online applications, and RFID electronic tag wristbands, with clinical record encryption and authentication, cross-chain trustworthy sharing, remote authorization, and other features. Additionally, in order to accomplish tailored privacy protection, a system for controlling the flow of private data using patients as the main source is proposed in this work. This mechanism is based on a biometric key and a secret algorithm. In order to establish reliable access and control, the master-slave multi-chain layered cross-chain paradigm based on the upgraded PBFT consensus algorithm for the main Chain and PoVT consensus algorithm for the slave Chain is employed
S. Ozcan and S. Unalan, "Blockchain as a General-Purpose Technology: Patentometric Evidence of Science, Technologies, and Actors," in IEEE Transactions on Engineering Management, vol. 69, no. 3, pp. 792-809, June 2022, doi: 10.1109/TEM.2020.3008859.
C. Xu, Y. Qu, T. H. Luan, P. W. Eklund, Y. Xiang and L. Gao, "A Lightweight and Attack-Proof Bidirectional Blockchain Paradigm for Internet of Things," in IEEE Internet of Things Journal, vol. 9, no. 6, pp. 4371-4384, 15 March15, 2022, doi: 10.1109/JIOT.2021.3103275.
H. Xiong et al., "On the Design of Blockchain-Based ECDSA With Fault-Tolerant Batch Verification Protocol for Blockchain-Enabled IoMT," in IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 5, pp. 1977-1986, May 2022, doi: 10.1109/JBHI.2021.3112693.
M. N. M. Bhutta et al., "A Survey on Blockchain Technology: Evolution, Architecture and Security," in IEEE Access, vol. 9, pp. 61048-61073, 2021, doi: 10.1109/ACCESS.2021.3072849.
W. Liang, D. Zhang, X. Lei, M. Tang, K. -C. Li and A. Y. Zomaya, "Circuit Copyright Blockchain: Blockchain-Based Homomorphic Encryption for IP Circuit Protection," in IEEE Transactions on Emerging Topics in Computing, vol. 9, no. 3, pp. 1410-1420, 1 July-Sept. 2021, doi: 10.1109/TETC.2020.2993032.
J. Ren, J. Li, H. Liu and T. Qin, "Task offloading strategy with emergency handling and blockchain security in SDN-empowered and fog-assisted healthcare IoT," in Tsinghua Science and Technology, vol. 27, no. 4, pp. 760-776, Aug. 2022, doi: 10.26599/TST.2021.9010046.
H. M. Kim, H. Turesson, M. Laskowski and A. F. Bahreini, "Permissionless and Permissioned, Technology-Focused and Business Needs-Driven: Understanding the Hybrid Opportunity in Blockchain Through a Case Study of Insolar," in IEEE Transactions on Engineering Management, vol. 69, no. 3, pp. 776-791, June 2022, doi: 10.1109/TEM.2020.3003565.
Y. Qu, S. R. Pokhrel, S. Garg, L. Gao and Y. Xiang, "A Blockchained Federated Learning Framework for Cognitive Computing in Industry 4.0 Networks," in IEEE Transactions on Industrial Informatics, vol. 17, no. 4, pp. 2964-2973, April 2021, doi: 10.1109/TII.2020.3007817.
S. Xu, X. Chen and Y. S. Khatri, F. A. Alzahrani, M. T. J. Ansari, A. Agrawal, R. Kumar and R. A. Khan, "A Systematic Analysis on Blockchain Integration With Healthcare Domain: Scope and Challenges," in IEEE Access, vol. 9, pp. 84666-84687, 2021, doi: 10.1109/ACCESS.2021.3087608.26, no. 6, pp. 845-856, Dec. 2021, doi: 10.26599/TST.2020.9010043.
J. Zhou, G. Feng and Y. Wang, "Optimal Deployment Mechanism of Blockchain in Resource-Constrained IoT Systems," in IEEE Internet of Things Journal, vol. 9, no. 11, pp. 8168-8177, 1 June1, 2022, doi: 10.1109/JIOT.2021.3106355.
X. Cai et al., "A Sharding Scheme-Based Many-Objective Optimization Algorithm for Enhancing Security in Blockchain-Enabled Industrial Internet of Things," in IEEE Transactions on Industrial Informatics, vol. 17, no. 11, pp. 7650-7658, Nov. 2021, doi: 10.1109/TII.2021.3051607.
Tharatipyakul and S. Pongnumkul, "User Interface of Blockchain-Based Agri-Food Traceability Applications: A Review," in IEEE Access, vol. 9, pp. 82909-82929, 2021, doi: 10.1109/ACCESS.2021.3085982.
S. K. Ezzat, Y. N. M. Saleh and A. A. Abdel-Hamid, "Blockchain Oracles: State-of-the-Art and Research Directions," in IEEE Access, vol. 10, pp. 67551-67572, 2022, doi: 10.1109/ACCESS.2022.3184726.
A. Omar, R. Jayaraman, M. S. Debe, K. Salah, I. Yaqoob and M. Omar, "Automating Procurement Contracts in the Healthcare Supply Chain Using Blockchain Smart Contracts," in IEEE Access, vol. 9, pp. 37397-37409, 2021, doi: 10.1109/ACCESS.2021.3062471.
M. S. Farooq, U. Iftikhar and A. Khelifi, "A Framework to Make Voting System Transparent Using Blockchain Technology," in IEEE Access, vol. 10, pp. 59959-59969, 2022, doi: 10.1109/ACCESS.2022.3180168.
S. -J. Hsiao and W. -T. Sung, "Employing Blockchain Technology to Strengthen Security of Wireless Sensor Networks," in IEEE Access, vol. 9, pp. 72326-72341, 2021, doi: 10.1109/ACCESS.2021.3079708.
T. Meng, Y. Zhao, K. Wolter and C. -Z. Xu, "On Consortium Blockchain Consistency: A Queueing Network Model Approach," in IEEE Transactions on Parallel and Distributed Systems, vol. 32, no. 6, pp. 1369-1382, 1 June 2021, doi: 0.1109/TPDS.2021.3049915.
T. H. Tran, H. L. Pham, T. D. Phan and Y. Nakashima, "BCA: A 530-mW Multicore Blockchain Accelerator for Power-Constrained Devices in Securing Decentralized Networks," in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 68, no. 10, pp. 4245-4258, Oct. 2021, doi: 10.1109/TCSI.2021.3102618.
S. E. Chang and Y. Chen, "When Blockchain Meets Supply Chain: A Systematic Literature Review on Current Development and Potential Applications," in IEEE Access, vol. 8, pp. 62478-62494, 2020, doi: 10.1109/ACCESS.2020.2983601.
L. Yan, S. Yin-He, Y. Qian, S. Zhi-Yu, W. Chun-Zi and L. Zi-Yun, "Method of Reaching Consensus on Probability of Food Safety Based on the Integration of Finite Credible Data on Block Chain," in IEEE Access, vol. 9, pp. 123764-123776, 2021, doi: 10.1109/ACCESS.2021.3108178.
J. Indumathi et al., "Block Chain Based Internet of Medical Things for Uninterrupted, Ubiquitous, User-Friendly, Unflappable, Unblemished, Unlimited Health Care Services (BC IoMT U6 HCS)," in IEEE Access, vol. 8, pp. 216856-216872, 2020, doi: 10.1109/ACCESS.2020.3040240.
H. Zhi, H. Ge and Y. Wang, "Cooperative Communication Method Based on Block Chain for a Large Number of Distributed Terminals," in IEEE Access, vol. 10, pp. 11679-11695, 2022, doi: 10.1109/ACCESS.2022.3145444.
X. Fu, H. Wang and Z. Wang, "Research on Block-Chain-Based Intelligent Transaction and Collaborative Scheduling Strategies for Large Grid," in IEEE Access, vol. 8, pp. 151866-151877, 2020, doi: 10.1109/ACCESS.2020.3017694.
L. Askari, F. Musumeci and M. Tornatore, "Reprovisioning for latency-aware dynamic service chaining in metro networks," in Journal of Optical Communications and Networking, vol. 12, no. 11, pp. 355-366, November 2020, doi: 10.1364/JOCN.400149.
D. Samanta et al., "Cipher Block Chaining Support Vector Machine for Secured Decentralized Cloud Enabled Intelligent IoT Architecture," in IEEE Access, vol. 9, pp. 98013-98025, 2021, doi: 10.1109/ACCESS.2021.3095297.
E. Ram and Y. Cassuto, "On the Decoding Performance of Spatially Coupled LDPC Codes With Sub-Block Access," in IEEE Transactions on Information Theory, vol. 68, no. 6, pp. 3700-3718, June 2022, doi: 10.1109/TIT.2022.3152104.
S. Khan, M. A. Irfan, A. Arif, A. Ali, Z. A. Memon and A. Khaliq, "Reversible-Enhanced Stego Block Chaining Image Steganography: A Highly Efficient Data Hiding Technique," in Canadian Journal of Electrical and Computer Engineering, vol. 43, no. 2, pp. 66-72, Spring 2020, doi: 10.1109/CJECE.2019.2938844.
R. G.S. and M. Dakshayini, "Block-chain Implementation of Letter of Credit based Trading system in Supply Chain Domain," 2020 International Conference on Mainstreaming Block Chain Implementation (ICOMBI), 2020, pp. 1-5, doi: 10.23919/ICOMBI48604.2020.9203485.
Veeraiah V., Kumar K. R., Lalitha K. P., Ahamad S., Bansal R. and Gupta A., (2022). Application of Biometric System to Enhance the Security in Virtual World. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 719-723.doi: 10.1109/ICACITE53722.2022.9823850.
Babu, S.Z.D. et al. (2022). Analysation of Big Data in Smart Healthcare. In: Gupta, M., Ghatak, S., Gupta, A., Mukherjee, A.L. (eds) Artificial Intelligence on Medical Data. Lecture Notes in Computational Vision and Biomechanics, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-19-0151-5_21
Bansal R., Gupta A., Singh R. and Nassa V. K., (2021). Role and Impact of Digital Technologies in E-Learning amidst COVID-19 Pandemic. 2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT), pp. 194-202.doi: 10.1109/CCICT53244.2021.00046.
Dushyant, K., Muskan, G., Gupta, A. and Pramanik, S. (2022). Utilizing Machine Learning and Deep Learning in Cyber security: An Innovative Approach”, in Cyber security and Digital Forensics, M. M. Ghonge, S. Pramanik, R. Mangrulkar,D. N. Le, Eds, Wiley, https://doi.org/10.1002/9781119795667.ch12
Gupta A., Singh R., Nassa V. K., Bansal R., Sharma P. and Koti K., (2021) Investigating Application and Challenges of Big Data Analytics with Clustering. 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), pp. 1-6.doi: 10.1109/ICAECA52838.2021.9675483.
Kaushik, K., Garg, M., Annu, Gupta, A. and Pramanik, S. (2021). Application of Machine Learning and Deep Learning in Cyber security: An Innovative Approach, in Cybersecurity and Digital Forensics: Challenges and Future Trends, M. Ghonge, S. Pramanik, R. Mangrulkar and D. N. Le, Eds, Wiley, 2021.
Pandey, B.K. et al. (2022). Effective and Secure Transmission of Health Information Using Advanced Morphological Component Analysis and Image Hiding. In: Gupta, M., Ghatak, S., Gupta, A., Mukherjee, A.L. (eds) Artificial Intelligence on Medical Data. Lecture Notes in Computational Vision and Biomechanics, vol 37. Springer, Singapore.https://doi.org/10.1007/978-981-19-0151-5_19
Pathania, V. et al. (2022). A Database Application of Monitoring COVID-19 in India. In: Gupta, M., Ghatak, S., Gupta, A., Mukherjee, A.L. (eds) Artificial Intelligence on Medical Data. Lecture Notes in Computational Vision and Biomechanics, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-19-0151-5_23
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya and A. Gupta, "A Review on Comparative study of 4G, 5G and 6G Networks," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 1830-1833, doi: 10.1109/IC3I56241.2022.10073385.
V. Jain, S. M. Beram, V. Talukdar, T. Patil, D. Dhabliya and A. Gupta, "Accuracy Enhancement in Machine Learning During Blockchain Based Transaction Classification," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 536-540, doi: 10.1109/PDGC56933.2022.10053213.
V. Talukdar, D. Dhabliya, B. Kumar, S. B. Talukdar, S. Ahamad and A. Gupta, "Suspicious Activity Detection and Classification in IoT Environment Using Machine Learning Approach," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 531-535, doi: 10.1109/PDGC56933.2022.10053312.
P. R. Kshirsagar, D. H. Reddy, M. Dhingra, D. Dhabliya and A. Gupta, "A Scalable Platform to Collect, Store, Visualize and Analyze Big Data in Real- Time," 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM), Uttar Pradesh, India, 2023, pp. 1-6, doi: 10.1109/ICIPTM57143.2023.10118183.
M. Dhingra, D. Dhabliya, M. K. Dubey, A. Gupta and D. H. Reddy, "A Review on Comparison of Machine Learning Algorithms for Text Classification," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 1818-1823, doi: 10.1109/IC3I56241.2022.10072502.
D. Mandal, A. Shukla, A. Ghosh, A. Gupta and D. Dhabliya, "Molecular Dynamics Simulation for Serial and Parallel Computation Using Leaf Frog Algorithm," 2022 Seventh International Conference on Parallel, Distributed and Grid Computing (PDGC), Solan, Himachal Pradesh, India, 2022, pp. 552-557, doi: 10.1109/PDGC56933.2022.10053161.
V. V. Chellam, S. Praveenkumar, S. B. Talukdar, V. Talukdar, S. K. Jain and A. Gupta, "Development of a Blockchain-based Platform to Simplify the Sharing of Patient Data," 2023 3rd International Conference on Innovative Practices in Technology and Management (ICIPTM), Uttar Pradesh, India, 2023, pp. 1-6, doi: 10.1109/ICIPTM57143.2023.10118194.
Lalitha Kumari, P. et al. (2023). Methodology for Classifying Objects in High-Resolution Optical Images Using Deep Learning Techniques. In: Chakravarthy, V., Bhateja, V., Flores Fuentes, W., Anguera, J., Vasavi, K.P. (eds) Advances in Signal Processing, Embedded Systems and IoT . Lecture Notes in Electrical Engineering, vol 992. Springer, Singapore. https://doi.org/10.1007/978-981-19-8865-3_55
Sindhwani, N. et al. (2023). Comparative Analysis of Optimization Algorithms for Antenna Selection in MIMO Systems. In: Chakravarthy, V., Bhateja, V., Flores Fuentes, W., Anguera, J., Vasavi, K.P. (eds) Advances in Signal Processing, Embedded Systems and IoT . Lecture Notes in Electrical Engineering, vol 992. Springer, Singapore. https://doi.org/10.1007/978-981-19-8865-3_54
Patil, A. ., & Govindaraj, S. K. . (2023). ADL-BSDF: A Deep Learning Framework for Brain Stroke Detection from MRI Scans towards an Automated Clinical Decision Support System. International Journal on Recent and Innovation Trends in Computing and Communication, 11(3), 11–23. https://doi.org/10.17762/ijritcc.v11i3.6195
Sofia Martinez, Machine Learning-based Fraud Detection in Financial Transactions , Machine Learning Applications Conference Proceedings, Vol 1 2021.
Jain, V., Beram, S. M., Talukdar, V., Patil, T., Dhabliya, D., & Gupta, A. (2022). Accuracy enhancement in machine learning during blockchain based transaction classification. Paper presented at the PDGC 2022 - 2022 7th International Conference on Parallel, Distributed and Grid Computing, 536-540. doi:10.1109/PDGC56933.2022.10053213 Retrieved from www.scopus.com
How to Cite
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.