Biomedical Data Security Using a Hybrid Encryption Approach Based on Fractional-Order Hyper-Chaotic Systems and DNA Coding

Deoxyribonucleic acid (DNA) cryptography is a notion which merges the principles of biotechnology and cryptography, situated at the intersection of mathematics, molecular biology and computer science. Correspondingly, DNA coding and DNA-based cryptography mark a significant paradigm toward secure information management by addressing information density, biological stability of DNA as well as inherent parallelism while considering the complexity and unpredictability of chaotic systems, paving the way for more effective processes of data encryption, steganography and secure storage. Biomedical data is regarded as one of the most sensitive types of data since patients’ medical data may contain their medical history, diagnoses, prescriptions, and so on. Thus, the security of biomedical data and information should be ensured to prevent unauthorized users from obtaining private data. Addressing these aspects and concerns, an innovative hybrid encryption algorithm integrating fractional-order hyper-chaotic systems with DNA-based cryptography is proposed in the present paper, considering fractional-order chaotic systems’ exhibiting more complex and richer dynamic behaviors compared to classical systems. The algorithm developed based on mathematical model established was applied to the heart disease dataset and evaluated through comprehensive experimental analyses. The results demonstrate that the encryption and decryption processes exhibit low latency, high entropy values and maintain data integrity with 100% accuracy. These findings indicate that the proposed hybrid encryption approach offers a robust and practical solution for real-time and high-security applications, particularly in the protection of sensitive biomedical data.