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

Area of Science:

• Health Informatics
• Cryptography
• Bioinformatics

Background:

• Decentralized systems offer enhanced security for sensitive data.
• Blockchain technology provides a transparent and immutable ledger for transactions.
• Traditional hashing algorithms may face challenges in computational complexity and security for large datasets.

Purpose of the Study:

• To develop and evaluate a novel genetic-based hashing algorithm for securing health data distribution records.
• To leverage blockchain technology for a secure, transparent, and tamper-proof health data management system.
• To assess the efficiency, security, and integrity of the proposed algorithm in a decentralized environment.

Main Methods:

• A genetic algorithm (GA) was employed to generate cryptographic keys for encryption and decryption.
• A 512-bit cryptographic hashing algorithm was modified for use in a secure decentralized network.
• The system utilizes blockchain to manage, secure, and validate health data distribution records.

Main Results:

• The genetic-based hashing algorithm demonstrated lower computational complexity and reduced space coverage.
• The proposed method achieved higher security and data integrity with a significant avalanche effect.
• Simulations confirmed the validity, immunity from fraud, and integrity of the data records.

Conclusions:

• The genetic-based hashing algorithm offers a robust solution for securing health data in decentralized environments.
• This approach enhances data protection against manipulation and corruption, ensuring reliable medical research.
• The integration of GA-generated keys with blockchain provides a secure and efficient framework for healthcare data management.