Paper 2026/1354

Adaptive Quantum-Resistant Hybrid Encryption Framework for Secure IoMT Edge Data Sharing

Abstract

The Internet of Medical Things (IoMT) is revolutionizing healthcare through real-time monitoring and personalized care, yet existing security solutions for resource-constrained IoMT devices often compromise between robust protection and computational efficiency. Additionally, various IoMT systems utilize different sets of encryption schemes, ranging from classical to post-quantum algorithms, tailored to their computational resources, operational constraints, and specific privacy challenges. This diversity highlights an urgent need for an adaptive and efficient, quantum-resistant security protocol applicable to these systems. We propose the Privacy-Preserving Hybrid Data Sharing ($P^2HDS$) framework, which integrates multiple classical and post-quantum encryption schemes to achieve strong security with enhanced efficiency. $P^2HDS$ formalizes a generalized hybrid encryption protocol that enables adaptive configuration based on security requirements and computational constraints. We employ game-theoretic analysis to model interactions between data owners and adversaries, determining the optimal combination of encryption schemes for data outsourcing to mitigate adversarial threats. Rigorous security analysis proves that $P^2HDS$ achieves indistinguishability under chosen-plaintext attack (IND-CPA) security in the random oracle model, provided at least one constituent scheme is IND-CPA-secure. Experimental results demonstrate that $P^2HDS$ delivers performance approximating the average of its constituent schemes while maintaining security comparable to the most secure component, making it a scalable, quantum-resistant, and adaptive solution for privacy-preserving IoMT edge applications.