Sustainable Approach to Data Security: Multi-Key Biometric Encryption and Cloud Storage for SDG-Focused Businesses

This paper presents the implementation and evaluation of a Multi-key Multi-modalities Biometric Encryption System designed for business enterprises, leveraging cloud storage for secure and scalable data management. The system integrates multiple biometric modalities fingerprint, iris scan, and face recognition to enhance data security through advanced multi-key encryption techniques, utilizing algorithms such as Advanced Encryption Standard (AES) and Rivest-Shamir-Adleman (RSA). The encrypted biometric data is securely stored in the cloud, providing enterprises with efficient storage solutions. The system's performance was evaluated across several parameters including encryption/decryption time, biometric match accuracy, data transfer speeds, energy consumption, cost, and user satisfaction. The results demonstrate that multi-modal systems offer superior accuracy and security compared to single-modality systems, reducing error rates and enhancing reliability. However, multi-modal authentication incurs higher costs, energy consumption, and slightly longer processing times. Despite these trade-offs, the system achieved high user satisfaction, particularly in high-security environments where data protection is a priority. The findings indicate that the proposed system is a viable solution for businesses seeking a secure, scalable, and efficient method of protecting sensitive data.