دانلود کتاب مدل‌های محاسباتی کوانتومی برای امنیت سایبری و ارتباطات بی‌سیم

Artificial intelligence, cybersecurity, and practical cryptography are just a few of the areas where quantum machine learning has the most potential. Advanced data encryption techniques are urgently needed as our growing reliance on the internet exposes us to threats brought on by cyber-attacks. Although many current encryption standards may not be breakable by current quantum-based machines, it is vital to keep ahead of the impending threats and prepare for sophisticated cyberattacks using quantum-proof solutions. The difficult issues that classical computers are unable to address, such as the techniques employed in data encryption, can be solved by quantum computers. Modern encryption techniques are based on mathematical formulas that would be impractically difficult for traditional computers to decrypt. Working tirelessly to create quantum-secure encryption techniques is the research goal. One possible method is for securely transferring a quantum key between two endpoints that makes use of the quantum physics qualities known as quantum key distribution (QKD). Before recent developments, this technique could only be used with fiber optic connections, but now quantum key transfer is also possible over the Internet. Although there are still many unsolved problems concerning quantum computing, it is evident that present methods of cybersecurity and encryption are at risk. We need to adapt the way we safeguard our data and take a defense-intensive strategy characterized by many layers of quantum-secure security to lessen the threat. To protect themselves from potential quantum threats, security-conscious organizations are actively looking for quantum-ready encryption solutions, including those provided by Quantum Exchange. Future quantum machines will exponentially boost computing power, creating new opportunities for improving cybersecurity. Both classical and quantum-based cyberattacks can be proactively identified and stopped by quantum-based cybersecurity before they harm. Complex math-based problems that support several encryption standards could be quickly solved using quantum machine learning. The traditional cryptography standards on classical computers, which rely on difficult mathematical calculations like prime factorization, would take millennia or more. However, these issues might be resolved by quantum machines in a manageable amount of time. Despite the lack of widespread commercial quantum devices, it is wise to plan for quantum-based cybersecurity difficulties and deal with present restrictions. The security and privacy of commercial organizations will greatly increase as a result of this preparation. For instance, today’s adversaries could penetrate private networks. When large-scale quantum machines are made commercially available in the future, this enormous computational capacity could be used to undermine networks and infrastructures by decrypting critical data. Quantum machine learning-based cybersecurity, especially in the context of quantum computing and quantum chaotic characteristics, presents stronger and more exciting chances for protecting important and sensitive information by outpacing these possible attacks. Through book chapters, academics, researchers, and scientists have contributed their ideas, concepts, and use cases on cutting- edge technologies like blockchain, quantum machine learning, cybersecurity, IoT, and SDN. The main purpose of this book is to publish the latest research papers focusing on problems and challenges in the areas of data transmission technology, computer algorithms, artificial intelligence (AI) based devices, computer technology, and their solutions to motivate researchers. This book serves as a ready reference for researchers and professionals working in the area of quantum computing models in communications, machine learning techniques, the healthcare industry, and IoT-enabled technologies.