In recent times, advanced developments in healthcare sector result in the generation of massive amounts of electronic health records (EHRs). EHR system enables the data owner to control his/her data and share it with designated people. The vast volume of data in the healthcare system makes it difficult for data to ensure security and diagnostic processes. To resolve these issues, this paper develops a new hyperledger blockchain enabled secure medical data management with deep learning (DL)-based diagnosis (HBESDM-DLD) model. The presented model involves distinct stages of operations such as encryption, optimal key generation, hyperledger blockchain-based secure data management, and diagnosis. The presented model allows the user to control access to data, permit the hospital authorities to read/write data, and alert emergency contacts. For encryption, SIMON block cipher technique is applied. At the same time, to improve the efficiency of the SIMON technique, a group teaching optimization algorithm (GTOA) is applied for the optimal key generation of the SIMON technique. Moreover, the sharing of medical data takes place using multi-channel hyperledger blockchain that utilizes a blockchain for storing patient visit data and for the medical institutions to record links for the EHRs saved in external databases. Once the data are decrypted at the receiving end, finally, variational autoencoder (VAE)-based diagnostic model is applied to detect the existence of the diseases. The performance validation of the HBESDM-DLD model takes place on benchmark medical dataset and the results are inspected under various performance measures. The experimental results proves that the HBESDM-DLD methodology is superior to state-of-the-art methods.

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Abstract. Cloud Computing offers an business model and it is tempting for companies to delegate their IT services, as well as data, to the Cloud. But in Cloud environment, lacking of cyber security users may suffer a serious data loss without any compensation for they have lost all their control on their data. Cyber security is the body of technologies and it is designed to protect networks, computers, programs and data from attack, damage or unauthorized access. Security audit is an important solution enabling trace back and analysis of any activities including data accesses, security breaches, application activities, and so on. Provable data possession (PDP) is an audit technique for ensuring the security of data in storage outsourcing. However, this existing audit schemes have focused on static data and the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection is very challenging task. For the cyber security we present a novel way implementation of a Trust Enhanced Third Party Auditor (TETPA), a trusted and easy-to-use auditor for Cloud environment. TETPA enables the Cloud Service Providers' accountability, and protects the Cloud users' benefits. Moreover our audit service is using for dynamic integrity verification in multi cloud storage. This scheme is based on the techniques, fragment structure, random sampling and index-hash table, Zero-Knowledge supporting provable updates to outsourced data and timely anomaly detection.