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. 2023 Feb 7:6.
doi: 10.30953/bhty.v6.244. eCollection 2023.

GAHBT: Genetic-Based Hashing Algorithm for Managing and Validating Health Data Integrity in Blockchain Technology

Fozia Hanif  1 , Urooj Waheed  2 , Rehan Shams  3 , Aisha Shareef  1
Affiliations

GAHBT: Genetic-Based Hashing Algorithm for Managing and Validating Health Data Integrity in Blockchain Technology

Fozia Hanif et al. Blockchain Healthc Today. .

Abstract

A method for managing, securing, and validating health data distribution records using a genetic-based hashing algorithm in a decentralized environment is presented in this research report. The rationale for choosing blockchain is to secure the transaction of health data and protect these data from manipulated fraudulent movement and corruption by a contributor to the chain, or any individual. Our approach uses technology that provides an efficient surveillance measure, including transparency of records, immunity from fraud, and protection from tampering, as well as sustaining the order of data. For medical research, the results here provide a genetic-based hashing algorithm for data security, which has lower computational complexity, low space coverage, higher security and integrity, and a high avalanche effect. The simulation will show the validity, immunity, and integrity of the data record. The technique modified in this secure decentralized network is a cryptographic hashing algorithm for 512 bits. In this study, a genetic algorithm (GA) is used to generate a key that must be used in the encryption and decryption of medical data. A GA is a metaheuristic approach inspired by the laws of genetics; and it is generally used to generate high-quality solutions for complex problems. Applications of GAs are possible in medical fields, such as radiology, oncology, cardiology, endocrinology, surgery, oncology, and radiotherapy in healthcare management.

Keywords: blockchain; decentralized technology; genetics; hashing; health data distribution; security; surveillance.

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Conflict of interest statement

The authors declare no potential conflict of interests at this time.

Figures

Fig. 1
Fig. 1
Process flow of the proposed model of GAHBT (genetic-based hashing algorithm for managing and validating health data integrity in blockchain technology).
Fig. 2
Fig. 2
Illustration of the padding procedure. The b-bit message is based on 64 bits. After that, it is appended under modulo 512 (divisible by 16 for working in hexadecimal). These two steps are taken from Professor Rivest’s study to construct the entered message input for digestion by annexing and padding the bits.
Fig. 3
Fig. 3
Flowchart showing the steps of GA (genetic algorithm).
Fig. 4
Fig. 4
Encryption procedure by using the first part of the key.
Fig. 5
Fig. 5
Relation between the execution time and health records in working consensus mechanism.
Fig. 6
Fig. 6
Relation between data transfer and the number of health records.
Fig. 7
Fig. 7
Relation between querying health records and execution time.
Fig. 8
Fig. 8
Relation between the number of health records and data transfer in GBs in the working consensus mechanism.
Fig. 9
Fig. 9
Relation between transmission of the number of health records and execution time as the number of medical centers increases.
Fig. 10
Fig. 10
Relation between transmission of the number of health records and execution time as the number of medical centers increases.
See this image and copyright information in PMC

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