Secure medical data storage in DPOS-hyper ledger fabric block chain using PM-ECC and L2-DWT

Abstract

Governments and individuals have taken extraordinary measures to protect the health of the people during the COVID pandemic. Stored medical data remains the main target for hackers, and hence it needs to be stored securely. To achieve this objective, this paper proposes a novel model using Delegated Proof of Stake-Hyper ledger Fabric Block Chain (DPOS-HFBC). Primarily, by employing LL Subbandeigen Value decomposition employed Discrete Wavelet Transform (L2-DWT), the patient’s Lung Computed Tomography (CT) image data are collected and embedded. For embedding, the patient’s name and ID are taken. In embedding, a Pseudorandom number generator using the Mersenne twister algorithm employed in Elliptic Curve Cryptography (PM-ECC) is applied for key encryption. It covered the image that was embedded with the original and then stored in DPOS-HFBC. Likewise, for authorization, every patient’s biometric ID was hashed and stored in DPOS-HFBC. Data requesters request data in the Interplanetary File System (IPFS) of DPOS-HFBC, and the attributes from the request are extracted and sent to the authority for verification. After verifying, the authority shares their biometric ID with the requester and this gets hashed and then verified in DPOS-HFBC. To show the model’s supremacy, the proposed method was evaluated and compared with existing methods.