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Blockchain Assisted Cloud Security and Privacy Preservation using Hybridized Encryption and Deep Learning Mechanism in IoT-Healthcare Application

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Abstract

The fundamental issue that happens in cloud computing is considered to be privacy when applying it in Ubiquitous healthcare systems, which rely on data aggregation and joint deep learning mechanisms between various parties. The users undergoing communication make the interaction between the cloud for performing the data exchange. The participants involved in the process are presented at different levels, and also their hope gets differ based on the interaction characteristics. However, it is highly challenging to build the basic platform for communication in the cloud environment. On the other hand, security solutions can be implemented to assuring the confidentiality of exchanging data. Therefore, in this proposed model, a secure outsourcing scheme using a deep learning framework is developed to provide cloud security and privacy preservation in the healthcare Internet of Things (IoT) environment. Different IoT devices are used for collecting the patient’s health data and storing it in the database. Initially, the medical data is garnered from the standard databases, and this is encrypted by using the Optimal Key-based Hybrid Elliptic Curve Cryptography with Fully Homomorphic Encryption (OK-HECCFHE). Here, the optimal key is generated using Hybrid Polar Bear-Ageist Spider Monkey Optimization (HPB-ASMO) algorithm. Then, the encrypted data is stored in the blockchain, and it gets decrypted by the appropriate user using the optimal key, and finally, the medical data prediction is done via the Optimized Deep Neural Network with a Gated Recurrent Unit (ODNN-GRU), where the parameters are optimized from the hybrid deep learning network to maximize the performance with the support of same HPB-ASMO. The experimental analysis is carried out to verify the performance of the developed model by using different evaluation metrics.

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Data Availability

The data underlying this article are available in Health Care Analytics database, at https://www.kaggle.com/datasets/abisheksudarshan/health-care-analytics: access date: 2023–04-10, and AV: Healthcare Analytics II, at https://www.kaggle.com/datasets/nehaprabhavalkar/av-healthcare-analytics-ii: access date: 2023–04-10.

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Acknowledgements

I would like to express my very great appreciation to the co-authors of this manuscript for their valuable and constructive suggestions during the planning and development of this research work

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Authors and Affiliations

  1. Department of Information Technology, E.G.S. Pillay Engineering College, Old, Nagore Main Rd, Thethi Village, Nagore, Nagapattinam, Tamil Nadu, 611002, India

    K. Raju

  2. Department of Computer Science and Engineering, R.M.D Engineering College, RMD College Road, Kavaraipettai, Tiruvallur, Tamil Nadu, 601206, India

    N. Ramshankar

  3. Department of Computer Science and Engineering, Chelairu Road Srinivas Nagar, Surathkal, Mangaluru, Karnataka, 574146, India

    J. Anvar Shathik

  4. Srinivas University, Mangaluru, India

    J. Anvar Shathik

  5. Department of Information Technology, E.G.S. Pillay Engineering College, Old Nagore Road, Thethi Village, Nagapattinam, 611002, India

    R. Lavanya

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All authors have made substantial contributions to conception and design, revising the manuscript, and the final approval of the version to be published. Also, all authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Raju, K., Ramshankar, N., Shathik, J.A. et al. Blockchain Assisted Cloud Security and Privacy Preservation using Hybridized Encryption and Deep Learning Mechanism in IoT-Healthcare Application. J Grid Computing 21, 45 (2023). https://doi.org/10.1007/s10723-023-09678-7

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