Post-Quantum Cybersecurity for AI-Driven Rural Healthcare Systems: A Framework for Protecting Economically Distressed U.S. Communities

Abstract

With AI now being used in rural healthcare across the United States, ensuring the security of these digital systems, especially in economically struggling communities, is crucial. Many healthcare communities utilize AI for diagnoses, online visits, and maintaining health records, but they often lack the same cybersecurity strength as busy cities. Due to the emergence of quantum computing, current methods for protecting sensitive healthcare information may be compromised. Therefore, the article proposes a specialized cybersecurity framework for AI-driven healthcare systems serving people in rural and underserved areas. It introduces post-quantum cryptographic (PQC) solutions, including lattice- and hash-based encryption, into healthcare data systems to protect them against future quantum attacks, maintain the feasibility of AI, and ensure compliance with HIPAA and NIST rules.
The model ensures that affordability, scalability, and ease of use are essential, making it suitable for areas where resources are scarce. Securing calls and messages in telehealth, strengthening AI-based diagnostic tools against cyberattacks, and protecting IoT medical devices used to monitor patients at home are top priorities. The framework was tested by simulating cyberattacks against typical rural healthcare architecture designs. Data show that PQC enhances the safety of systems and reduces risks with no drop in performance. It addresses the challenge of technology and highlights the need to protect vulnerable individuals from emerging cybersecurity threats. Due to its replicable model, this research serves as a key resource for anyone seeking to safeguard the digital transformation of rural healthcare in the quantum era.