Blockchain- Based Secure and Efficient Scheme for Medical Data

Authors

  • Manish Gupta Madan Mohan Malaviya University of Technology image/svg+xml
  • Rajendra Kumar Dwivedi Madan Mohan Malaviya University of Technology image/svg+xml

DOI:

https://doi.org/10.4108/eetsis.3235

Keywords:

IoT, Data, Fog Computing, Hyperledger Fabric, Hash Value

Abstract

Internet of Things (IoT) fog nodes are distributed near end-user devices to mitigate the impacts of low delay, position awareness, and spatial spread, which aren't permitted by numerous IoT apps. Fog computing (FC) also speeds up reaction times by decreasing the quantity of data sent to the cloud. Despite these advantages, FC still has a lot of work to do to fulfill security and privacy standards. The constraints of the FC resources are the cause of these difficulties. In reality, FC could raise fresh concerns about privacy and security. Although the Fog security and privacy problems have been covered in several articles recently, most of these studies just touched the surface of these difficulties. This paper provides a unique solution for the authentication of data by using hyperledger fabric. The fog layer store data transferred by the IoT layer and calculate the hash value. These hash values are now stored in hyperledger fabric for authentication purposes. The proposed model results compared with lewako’s and Fan’s scheme and found that the proposed model has 25.00 % less encryption time, 09.3 % less decryption time, 17.48 % less storage overhead, and 23.38 % less computation cost as compared to Fan’s scheme.

References

R. Mahmud, R. Kotagiri, R. Buyya, Fog computing: a taxonomy, survey and future directions, in: Internet of Everything: Algorithms, Methodologies, Technologies and Perspectives, Springer, Singapore, 2018, pp. 103–130.

Q.-V. Pham, F. Fang, V.N. Ha, M. Le, Z. Ding, L.B. Le, W.-J. Hwang, A survey of multi-access edge computing in 5G and beyond: fundamentals, technology integration, and state-of-the-art, arXiv preprint, arXiv:1906.08452, 2019.

Abbasi BZ, Shah MA. Fog computing: security issues, solutions and robust practices. Paper presented at: Proceedings of 2017 23rd International Conference on Automation and Computing (ICAC); 2017: 1–6

Sagiroglu S, Sinanc D (2013) Big data: A review. In: Collaboration Technologies and Systems (CTS), 2013 International Conference On. IEEE. pp 42–47

Bonomi F, Milito R, Zhu J, Addepalli S (2012) Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile CC. ACM. pp 13–16

Sareen P, Kumar P (2016) The fog computing paradigm. Int J Emerging Technol Eng Res 4:55–60

Vaquero LM, Rodero-Merino L (2014) Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Comput Commun Rev 44(5):27–32

Saharan K, Kumar A (2015) Fog in comparison to cloud: A survey. Int J Comput Appl 122(3):10–12

Cisco (2015) Cisco Fog Computing Solutions: Unleash the Power of the Internet of Things. Online: https://www.cisco.com/c/dam/en_us/ solutions/trends/iot/docs/computing-solutions.pdf. Accessed 13 Dec 2016

Bushra J et al (2020) A job scheduling algorithm for delay and performance optimization in fog computing. Concurren Comput Pract Exper 32(7):5581

Q. Zhou, H. Huang, Z. Zheng, and J. Bian, “Solutions to scalability of BC: A survey,” IEEE Access, vol. 8, pp. 16 440–16 455, 2020.

W. Viriyasitavat and D. Hoonsopon, “BC characteristics and consensus in modern business processes,” Journal of Industrial Information Integration, vol. 13, pp. 32–39, Mar. 2019.

F. Casino, T. K. Dasaklis, and C. Patsakis, “A systematic literature review of BC-based applications: current status, classification and open issues,” Telematics and Informatics, vol. 36, pp. 55–81, Mar. 2019

https://www.ibm.com/in-en/topics/hyperledger

https://aws.amazon.com/BC/what-is-hyperledger-fabric/

L. Lin, T. Liu, S. Li, C. M. Sarathchandra Magurawalage, and S. Tu. Priguarder: A privacy-aware access control approach based on attribute fuzzy grouping in cloud environments. IEEE Access, 6:1882–1893, 2018.

K. Seol, Y. Kim, E. Lee, Y. Seo, and D. Baik. Privacy-preserving attribute-based access control model for xml-based electronic health record system. IEEE Access, 6:9114–9128, 2018.

Q. Liu, H. Zhang, J. Wan, and X. Chen. An access control model for resource sharing based on the role-based access control intended for multi-domain manufacturing internet of things. IEEE Access, 5:7001–7011, 2017

S. Chatterjee, S. Roy, A. K. Das, S. Chattopadhyay, N. Kumar, A. G. Reddy, K. Park, and Y. Park. On the design of fine grained access control with user authentication scheme for telecare medicine information systems. IEEE Access, 5:7012–7030, 2017.

K. Zhang, Y. Mao, S. Leng, Y. He, and Y. Zhang. Mobile-edge computing for vehicular networks: A promising network paradigm with predictive off-loading. IEEE Vehicular Technology Magazine, 12(2):36–44, 2017

Mengting Liu, Richard Yu, Yinglei Teng, Victor CM Leung, and Mei Song. Computation offloading and content caching in wireless BC networks with mobile edge computing. IEEE Transactions on Vehicular Technology, 2018

R. Yu, J. Ding, X. Huang, M. Zhou, S. Gjessing, and Y. Zhang. Optimal resource sharing in 5g-enabled vehicular networks: A matrix game approach. IEEE Transactions on Vehicular Technology, 65(10):7844–7856, 2016.

K. Zhang, S. Leng, Y. He, S. Maharjan, and Y. Zhang. Mobile edge computing and networking for green and low-latency internet of things. IEEE Communications Magazine, 56(5):39–45, 2018.

Z. Li, J. Kang, R. Yu, D. Ye, Q. Deng, and Y. Zhang. Consortium BC for secure energy trading in industrial internet of things. IEEE Transactions on Industrial Informatics, 14(8):3690–3700, Aug 2018

J. Kang, R. Yu, X. Huang, S. Maharjan, Y. Zhang, and E. Hossain. Enabling localized peer-to-peer electricity trading among plugin hybrid electric vehicles using consortium BCs. IEEE Transactions on Industrial Informatics, 13(6):3154–3164, Dec 2017.

V. Sharma, I. You, F. Palmieri, D. Jayakody, and J. Li. Secure and energy-efficient handover in fog networks using BC-based DMM. IEEE Communications Magazine, 56(5):22–31, 2018

H. Liu, Y. Zhang, and T. Yang. BC-enabled security in electric vehicles cloud and edge computing. IEEE Network, 32(3):78–83, 2018

Y. Zhang and N. Ansari. Hero: Hierarchical energy optimization for data center networks. IEEE Systems Journal, 9(2):406–415, 2015.

Salvatore J. Stolfo, Malek Ben Salem, Angelos D. Keromytis. Fog Computing: Mitigating Insider Data Theft Attacks in the Cloud. EE Symposium on Security and Privacy: 125-128

Shan Chen, Mi Wen, Rongxing Lu. Jinguo Li, Sijia Chen. Achieve Revocable Access Control for Fog-based Smart Grid System. IEEE 90th Vehicular Technology Conference, 2019

K. Fan, J. Wang, X. Wang, H. Li, and Y. Yang, “Secure, efficient and revocable data sharing scheme for vehicular fogs,” Peer-to-Peer Networking and Applications, vol. 11, no. 4, pp. 766–777, 2018.

A. Al Omar, M. S. Rahman, A. Basu, and S. Kiyomoto, “MediBchain: A BC based privacy preserving platform for healthcare data,” in Proc. Int. Conf. Secur., Privacy Anonymity Comput., Commun. Storage, 2017, pp. 534–543.

G. Dagher, J. Mohler, M. Milojkovic, and B. Praneeth, “Ancile: Privacypreserving framework for access control and interoperability of electronic health records using BC technology,” Sustain. Cities Soc., vol. 39, pp. 283–297, May 2018

S. Wang et al., “BC-powered parallel healthcare systems based on the ACP approach,” IEEE Trans. Comput. Social Syst., vol. 5, no. 4, pp. 942–950, Dec. 2018.

J. Xu et al., “Healthchain: A BC-based privacy preserving scheme for large-scale health data,” IEEE Internet Things J., vol. 6, no. 5, pp. 8770–8781, Oct. 2019.

S. Tanwar, K. Parekh, and R. Evans, “BC-based electronic healthcare record system for healthcare 4.0 applications,” J. Inf. Secur. Appl., vol. 50, Feb. 2020, Art. no. 102407.

T. A. Rahoof and V. R. Deepthi, “HealthChain: A secure scalable health care data management system using BC,” in Proc. Int. Conf. Distrib. Comput. Internet Technol., 2020, pp. 380–391.

B. Zaabar, O. Cheikhrouhou, F. Jamil, M. Ammi, and M. Abid, “HealthBlock: A secure BC-based healthcare data management system,” Comput. Netw., vol. 200, Dec. 2021, Art. no. 108500.

H. M. Hussien, S. M. Yasin, N. I. Udzir, M. I. H. Ninggal, and S. Salman, “BC technology in the healthcare industry: Trends and opportunities,” J. Ind. Inf. Integration, vol. 22, Jun. 2021, Art. no. 100217.

P. P. Ray, N. Kumar, and D. Dash, “BLWN: BC-based lightweight simplified payment verification in IoT-assisted e-healthcare,” IEEE Syst. J., vol. 15, no. 1, pp. 134–145, Mar. 2020.

Y. S. Rao, “A secure and efficient ciphertext-policy attribute-based signcryption for personal health records sharing in CC,” Future Gener. Comput. Syst., vol. 67, pp. 133–151, Feb. 2017.

G. Li, M. Dong, L. T. Yang, K. Ota, J. Wu, and J. Li, “Preserving edge knowledge sharing among IoT services: A BC-based approach,” IEEE Trans. Emerg. Topics Comput. Intell., vol. 4, no. 5, pp. 653–665, Oct. 2020

Chenthara, S., Ahmed, K., Wang, H., Whittaker, F. (2020). A Novel Blockchain Based Smart Contract System for eReferral in Healthcare: HealthChain. In: Huang, Z., Siuly, S., Wang, H., Zhou, R., Zhang, Y. (eds) Health Information Science. HIS 2020. Lecture Notes in Computer Science(), vol 12435. Springer, Cham. https://doi.org/10.1007/978-3-030-61951-0_9

Chenthara, S., Ahmed, K., Wang, H., Whittaker, F., & Chen, Z. (2020). Healthchain: A novel framework on privacy preservation of electronic health records using blockchain technology. PLOS ONE, 15(12), e0243043. https://doi.org/10.1371/journal.pone.0243043

You, M., Yin, J., Wang, H. et al. A knowledge graph empowered online learning framework for access control decision-making. World Wide Web 26, 827–848 (2023). https://doi.org/10.1007/s11280-022-01076-5

You, M., Yin, J., Wang, H., Cao, J., Miao, Y. (2021). A Minority Class Boosted Framework for Adaptive Access Control Decision-Making. In: Zhang, W., Zou, L., Maamar, Z., Chen, L. (eds) Web Information Systems Engineering – WISE 2021. WISE 2021. Lecture Notes in Computer Science(), vol 13080. Springer, Cham. https://doi.org/10.1007/978-3-030-90888-1_12

H. Wang and L. Sun, "Trust-Involved Access Control in Collaborative Open Social Networks," 2010 Fourth International Conference on Network and System Security, Melbourne, VIC, Australia, 2010, pp. 239-246, doi: 10.1109/NSS.2010.13.

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Published

28-06-2023

How to Cite

1.
Gupta M, Dwivedi RK. Blockchain- Based Secure and Efficient Scheme for Medical Data . EAI Endorsed Scal Inf Syst [Internet]. 2023 Jun. 28 [cited 2024 Dec. 26];10(5). Available from: https://publications.eai.eu/index.php/sis/article/view/3235