Data-Driven Predictive Healthcare: A Systematic Review Of Analytics Technologies And Clinical Applications

Abstract

This study addresses the pressing challenge of designing authentication mechanisms that remain secure against emerging cryptographic threats while operating within the severe resource constraints of wireless body area networks, Internet of Things (IoT) devices, and embedded healthcare systems. Existing multi-factor authentication solutions largely depend on asymmetric cryptography, such as RSA, ECC, and Diffie–Hellman, which are unsuitable for long-term security in the presence of advanced cryptanalytic capabilities and are impractical for ultra-low-power platforms owing to their computational and energy overhead. In contrast, the proposed framework demonstrates that a carefully engineered symmetric-only architecture, based on enlarged key sizes and modern cryptographic primitives, can deliver strong security guarantees with minimal latency and energy consumption. By leveraging AES-256, SHA3-256, and HMAC-SHA3, the protocol achieves near real-time authentication while maintaining robust resistance against both classical and advanced adversarial models. Extensive experimental evaluation confirms its deployability on constrained hardware, and formal security analysis verifies essential properties, such as mutual authentication, session key secrecy, freshness, and forward secrecy. Comparative benchmarking further positions the proposed solution as a practical middle ground between legacy schemes lacking future resilience and heavyweight cryptographic approaches that exceed the capabilities of embedded systems. Beyond technical validation, the framework offers significant practical value across multiple critical domains, including healthcare infrastructure, industrial Internet of Things, financial services, and smart city ecosystems, where long device lifetimes, strict energy budgets, and stringent latency requirements coexist with high security demands. While certain limitations remain, such as inherent constraints in biometric entropy, dependence on physical tamper resistance, and limited interoperability with public-key infrastructures, the modular and crypto-agile design enables gradual enhancement as standards and hardware evolve. The framework thus provides an immediately deployable solution while laying a flexible foundation for future integration of advanced key management, adaptive security policies, and emerging cryptographic technologies. Overall, this work demonstrates that security architectures can be rethought to balance resilience, efficiency, and practicality, ensuring sustainable protection for sensitive data and critical systems in next-generation computing environments.