Blind Quantum Artificial IntelligencePowered Cybersecurity

This essential guide provides the definitive, cutting-edge blueprint for engineering quantum-resistant, AI-driven security frameworks that neutralize advanced cyber threats in real time.

The convergence of quantum computing and artificial intelligence is fundamentally changing the cybersecurity landscape, replacing classical defense models with predictive, quantum-resistant frameworks capable of neutralizing advanced threats in real time. This book addresses the critical need for advanced security frameworks as traditional encryption mechanisms prove increasingly inadequate against evolving cyber threats. By examining the convergence of quantum artificial intelligence, quantum computing, and advanced threat detection algorithms, the text delineates next-generation paradigms capable of processing complex, large-scale data streams to deliver real-time resilience across high-stakes domains such as finance, healthcare, and defense. The work explores the computational intricacies driving AI-driven security protocols and demonstrates how integrating quantum AI techniques into distributed network architectures strengthens infrastructure, mitigates vulnerabilities, and safeguards economic growth. This comprehensive reference serves as an essential resource for academics, researchers, and industry professionals in network security seeking to engineer resilient, quantum-resistant architectures for next-generation digital ecosystems.

Abhishek Kumar, PhD, is an Assistant Director and Associate Professor in the Computer Science and Engineering Department at Chandigarh University, Punjab, India. He has authored seven books, edited 51 books, and published more than 170 works in reputable, peer-reviewed national and international journals, books, and conference proceedings. His research areas include artificial intelligence, renewable energy, image processing, computer vision, data mining, and machine learning.

Hemant Kumar Saini, PhD, is a Postdoctoral Fellow at Lincoln University, Malaysia, and works in the Parul School of Engineering and Technology at Parul University, India. He has more than 12 years of teaching experience and has published six books and several articles in renowned journals and conference proceedings. His research interests include wireless networks, soft computing, deep learning, machine learning, the Internet of Things, Industry 4.0, and smart contracts.

Pramod Singh Rathore, PhD, is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University Jaipur. With more than 12 years of academic teaching experience, he has published more than 85 papers in reputable, peer-reviewed national and international journals, books, and conference proceedings. His research interests include NS2, computer networks, and mining.

S. Oswalt Manoj, PhD, is an Associate Professor in the Department of Computer Science and Engineering at Sri Krishna College of Engineering and Technology, Tamil Nadu, India. He has authored one book, edited two books, and published more than 100 works in reputable, peer-reviewed national and international journals, books, and conference proceedings. His research areas include big data analytics, artificial intelligence, computer vision, machine learning, deep learning, and cloud computing.