Quantum Shield for AI Security
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Edited by:
Aleem Ali
, Puneet Kumar , Shaweta Sachdeva , Rajkumar Sarma and Nawaf R. Alharbe
About this book
The book explores how quantum computing can protect AI systems from sophisticated adversarial threats. As AI applications grow in sectors like finance, healthcare, and critical infrastructure, vulnerabilities such as data poisoning and model inversion pose significant security risks. This book investigates how quantum methods can effectively counter these challenges.
Distinct from existing literature, it combines theoretical insights with practical applications, covering quantum-enhanced cryptography, quantum machine learning for threat detection, and advanced algorithms tailored for AI. It provides actionable solutions for AI practitioners while also meeting the academic needs of researchers with rigorous mathematical treatments.
The book is targeted at academic researchers, professionals, and graduate students in computer science interested in AI and quantum computing. It goes beyond mathematical concepts to bridge quantum theory and its practical applications across sciences and industries. By offering both foundational principles and advanced quantum defense applications, this book serves as a vital resource for those developing AI systems with robust, quantum-enhanced security.
- Provides practical examples and case studies demonstrating the application of quantum-enhanced security measures.
- It will offer a robust, multi-disciplinary approach to adversarial defense strategies
Author / Editor information
Dr. Aleem Ali is a Professor at Chandigarh University with a focus on Quantum Computing, Machine Learning, and AI security. He has published extensively in top-tier journals and conferences, contributing significantly to the advancement of secure AI systems.
Dr. Puneet Kumar is a seasoned researcher with expertise in Quantum Computing and its applications in AI security. He has over 20 years of academic experience and has authored multiple patents and research papers.
Dr. Shaweta Sachdeva specializes in AI, Machine Learning, and Quantum Computing with over 19 years of academic experience. She has filed two patents and published 17 research papers, including contributions to the security aspects of AI.
Dr. Rajkumar Sarma is a Postdoctoral Researcher in University of Limerick (Public University). His research interests are in Quantum Technology, Network security, and AI.
Dr. Nawaf R. Alharbe is a Professor at Taibah University, with research interests in Quantum Computing, cybersecurity, and AI. He has been a key contributor to several high-impact research projects and publications in the field.
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Frontmatter
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Preface
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Contents
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List of contributing authors
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Chapter 1 Quantum blockchain and secure data flow
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Chapter 2 Adversarial machine learning and AI security: safeguarding Industry 4.0
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Chapter 3 Quantum twin shield: harnessing quantum-enhanced digital twins to secure the future of artificial intelligence against quantum-era threats
49 -
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Chapter 4 Quantum computing threats to AI security
73 -
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Chapter 5 Quantum-resistant cryptography in quantum twin shield architecture
117 -
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Chapter 6 A hybrid quantum-inspired model for sustainable electrification strategy: an energy-aware planning approach for cost-optimized data centers
135 -
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Chapter 7 Leveraging quantum decoy system for advanced threat detection in generative AI systems
151 -
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Chapter 8 Ethical and privacy challenges in building a quantum shield for AI security
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Chapter 9 Innovations in smart healthcare: advanced monitoring technologies and their impact on patient care
199 -
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Chapter 10 Quantum computing and healthcare software security: a novel hybrid evaluation framework
223 -
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Chapter 11 Exploring transformative potential and addressing ethical and privacy challenges in quantum-inspired AI system
247 -
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Chapter 12 A hybrid quantum-classical approach for fruit classification and calorie prediction using machine learning
273 -
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About the Editors
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Index
303 -
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De Gruyter series in quantum computing
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