Block-healthnet: security based healthcare system using block-chain technology
- PDF / 2,021,524 Bytes
- 19 Pages / 439.37 x 666.142 pts Page_size
- 83 Downloads / 190 Views
Block‑healthnet: security based healthcare system using block‑chain technology R. Shanthapriya1 · V. Vaithianathan1 Accepted: 23 September 2020 © Springer Nature Limited 2020
Abstract The health care systems are established widely to treat the patients through continuous monitoring and evaluation. There is a need for aggregating the health data for their long-term benefits. The cloud-based health care system is established to meet the demand of data aggregation. However, the privacy of the data in the cloud framework is under threat. For protecting and maintaining the privacy of the health records in cloud health care systems, several security frameworks are proposed. In most cases the proposed model lacks complete robustness and some are resulting in high computation and communication overheads. A block-chain based data securing technique is proposed with user and doctor block in the health care ecosystem to protect the medical health records. The proposed system employs the AES cryptography to perform the cryptic operation and block chaining it through the hash keys. Additionally, the proposed healthcare ecosystem includes prediction model to diagnose the disease of patient with the deep learning algorithm. The performance analysis of the proposed framework is analyzed over the security and prediction parameters. The results attained from proposed framework shows relatively better security performance than the earlier models. Keywords Privacy · Health records · AES · Block-chain · Prediction · Security
Introduction Health care (HC) is one of the fundamental requirements for any people in the world. With years there is a swift rise in chronic illness among people that mounts more stress over the present HC system (HCS) (Akpakwu et al. 2017). Additionally, there * R. Shanthapriya [email protected] V. Vaithianathan [email protected] 1
ECE Department, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Tamilnadu 603110, India Vol.:(0123456789)
R. Shanthapriya, V. Vaithianathan
are no adequate facilities to monitor patient’s previous medical information (Zhu et al. 2018). Accurate early prediction of disease can provide the opportunity for better treatment and increase the life span of the people (Mehmood et al. 2017; Li et al. 2017). To improve efficiency and accuracy, disease risk assessment and prediction performed on smart healthcare system (Pasluosta et al. 2015). Generally, the data are sent to perform the processing, aggregation and finally to reach the healthcare provider for the purpose of diagnosing the health status of individuals. However, the small electronic devices with low power consumption have limited storage and computing capacity. Due to this drawback, there is a need to assist additional device for effective computing and storage (Redondi et al. 2013). Cloud server is one of the common devices for outsourcing the electronic records of personal health data (Zhang et al. 2018). The efficiency improvement and cost reduction are achieved by the cloud-assisted hea
Data Loading...
