Quantum AI's health data security and governance: Safe and fair?

Manoj Kumar Pandey, Jyoti Upadhyay, Naresh Kumar Kar +1 more

Ramasamy Mariappan

Nowadays, quantum computing is evolving in computing algorithms and cryptography applications. Quantum cryptography is an ideal alternative to traditional cryptography algorithms, as it is provable and computationally secure. Quantum key distribution (QKD) is the heart of quantum cryptography, making secure key distribution. The QKD provides a promising solution for ensuring the secure transmission of electronic health records (EHRs). QKD provides information-theoretic security by utilizing the concepts of quantum physics, which makes it impervious to possible dangers from quantum computing. Numerous research projects that combine QKD with blockchain technology to improve data security and integrity have emphasized how important this capability is for safeguarding private health information. This book chapter explores the application of post-quantum cryptography in the secure transmission of EHR applied with the quantum safe blockchain network (QSBN). This chapter proposes a framework for effective key management using QKD and blockchain-based authentication, ensuring secure transmission of EHR between healthcare users and content servers through dedicated quantum channels.

M N Faruk, I. Manimozhi

Quantum computing poses a severe threat to standard digital security protocols, leaving artificial intelligence (AI) data pipelines and decision-support systems highly exposed. As large-scale quantum attacks become computationally feasible, the public-key cryptography currently securing data transmission will likely fail. This vulnerability threatens sectors heavily reliant on AI—including finance, healthcare, and critical infrastructure escalating the probability of data breaches, integrity losses, and compliance failures. To address these interconnected security, governance, and ethical hurdles, this paper introduces the Integrated Quantum-Resilient AI Framework (IQRAI). IQRAI establishes a structured governance model combining proactive quantum risk assessments, post-quantum cryptography (PQC), and continuous security monitoring. A core focus of the framework is balancing cryptographic migration with strict ethical requirements, specifically data privacy, algorithmic transparency, fairness, and auditability. Furthermore, the study reviews ongoing global standardization efforts for PQC transitions to define baseline requirements for sustained system resilience. By comparing existing mitigation models across metrics of operational friction, implementation difficulty, and security yield, the research identifies a critical operational gap. The analysis demonstrates that merely swapping cryptographic algorithms is insufficient for achieving quantum-resilient AI; securing these systems demands a unified approach that links security engineering, ethical oversight, and regulatory adherence. Ultimately, this work delivers a strategic roadmap for organizations to systematically harden their AI ecosystems against quantum threats while maintaining operational trust and legal compliance.

Hossein Hassani, Leila Marvian Mashhad, Steve MacFeely

Prashant Nair, Sunita Patil

Sarvapriya M. Tripathi, Himanshu Upadhyay, Jayesh Soni

With the advent of Healthcare 4.0, there is increased interest from researchers the world over in the application of modern, cutting-edge Artificial Intelligence (AI) and Quantum Artificial Intelligence (QAI) algorithms in solving healthcare challenges. The era of Quantum Computing (QC) promises to bring significant advancements in several areas of healthcare such that it may be sensible to give this hybrid Quantum/Classical paradigm its own name-Healthcare4Q. The potential of QC will extend the reach of Healthcare4Q with the help of diverse technologies such as quantum-enabled wearables, quantum-secure transfer and storage of data, and quantum computing at edge, fog, and cloud. All of these technologies promise to catapult Healthcare4Q to become the most capable healthcare framework in the advancement of medical innovations and improvement of patient care. An integral part of a person's health lies in cardiovascular health, and thus prioritizing and optimizing cardiovascular health remains vital to the broader goals of public health and healthcare sustainability. In this study, under the paradigm of Healthcare4Q, we propose a framework called the Quantum AIdriven Heart Health Framework (QAIHHF) that can provide advanced predictive intelligence to healthcare providers by utilizing historical and real-time data and processing capabilities proposed in Healthcare4Q. We show that when applied to various diagnostics and health indicators such as ECG data, the Quantum AI provides accuracy at a level equal to or higher as compared to the classical methods thus proving itself to be the critical component that will herald the era of Healthcare4Q.