The accelerating pace of quantum computing has brought both extraordinary opportunities and unprecedented risks. While quantum algorithms promise breakthroughs in optimization, simulation, and artificial intelligence, they also threaten the very foundations of today’s digital security. In particular, machine learning systems—now integral to finance, healthcare, defense, and critical infrastructure—are vulnerable to adversarial exploitation in a quantum-enabled world.
This book, Post-Quantum AI: Building Secure Machine Learning Systems in the Quantum Era, emerges from the recognition that we must prepare AI for a future where quantum attacks are not theoretical but inevitable. My goal is to provide a framework that bridges cutting-edge cryptographic research with the practical realities of AI deployment, ensuring that security, privacy, and trust are preserved as we transition into the quantum era.
The text is written for a diverse audience: researchers exploring the intersection of cryptography and machine learning, engineers designing next-generation AI systems, and policymakers tasked with setting international standards for secure technology. Each chapter blends theoretical grounding with applied case studies, from finance and supply chain optimization to drug discovery and communication networks. By integrating ethics, governance, and regulation alongside algorithms and architectures, the book seeks to provide a holistic perspective that is urgently needed.
This project represents the culmination of years of research and collaboration across academia, industry, and government initiatives. I am deeply grateful to my colleagues, mentors, and reviewers whose insights helped shape this work. Their contributions reinforced my conviction that building secure AI systems is not just a technical challenge but a societal imperative.
As you read, I invite you to view this book not only as a guide to technology but as a call to action. Preparing AI for the quantum era is a shared responsibility, and I hope these pages will serve as both a roadmap and an inspiration for the innovators, leaders, and practitioners who will carry this mission forward.
Author(s)
Amit Taneja
Vellore Institute of Technology, Tamil Nadu, India.
ISBN 978-93-88417-99-0 (Print)
ISBN 978-93-88417-05-1 (eBook)
DOI: https://doi.org/10.9734/bpi/mono/978-93-88417-99-0
The accelerating pace of quantum computing has brought both extraordinary opportunities and unprecedented risks. While quantum algorithms promise breakthroughs in optimization, simulation, and artificial intelligence, they also threaten the very foundations of today’s digital security. In particular, machine learning systems—now integral to finance, healthcare, defense, and critical infrastructure—are vulnerable to adversarial exploitation in a quantum-enabled world.
This book, Post-Quantum AI: Building Secure Machine Learning Systems in the Quantum Era, emerges from the recognition that we must prepare AI for a future where quantum attacks are not theoretical but inevitable. My goal is to provide a framework that bridges cutting-edge cryptographic research with the practical realities of AI deployment, ensuring that security, privacy, and trust are preserved as we transition into the quantum era.
The text is written for a diverse audience: researchers exploring the intersection of cryptography and machine learning, engineers designing next-generation AI systems, and policymakers tasked with setting international standards for secure technology. Each chapter blends theoretical grounding with applied case studies, from finance and supply chain optimization to drug discovery and communication networks. By integrating ethics, governance, and regulation alongside algorithms and architectures, the book seeks to provide a holistic perspective that is urgently needed.
This project represents the culmination of years of research and collaboration across academia, industry, and government initiatives. I am deeply grateful to my colleagues, mentors, and reviewers whose insights helped shape this work. Their contributions reinforced my conviction that building secure AI systems is not just a technical challenge but a societal imperative.
As you read, I invite you to view this book not only as a guide to technology but as a call to action. Preparing AI for the quantum era is a shared responsibility, and I hope these pages will serve as both a roadmap and an inspiration for the innovators, leaders, and practitioners who will carry this mission forward.