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Quantum computing systems are powerful for allowing a client to perform any quantum computations from a remote quantum server while concealing the structure and content of the computation fall under the category of blind quantum computing (BQC). In BQC, the client delegates the quantum processing to one or more powerful quantum servers while retaining privacy over the input, computation and output. This makes it suitable for secure quantum cloud computing. This feature is powerful to ensure that even untrusted servers cannot learn the details of the user's computation. With quantum computing, there is a fast-growing need to transition from general-purpose quantum systems to customized architectures tailored to specific application requirements. This transition is critical while considering sustainability goals and financial limitations. With this advanced computing architecture, a custom system can optimize energy use, hardware complexity, and resource allocation to better serve individual user needs while staying within budgetary boundaries.
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 researcher...
This book constitutes the refereed proceedings of the First International Conference on Advances in Computing and Data Sciences, ICACDS 2016, held in Ghaziabad, India, in November 2016. The 64 full papers were carefully reviewed and selected from 502 submissions. The papers are organized in topical sections on Advanced Computing; Communications; Informatics; Internet of Things; Data Sciences.
GANs represent a generative model leveraging the growing power of deep learning (DL) algorithms. This book presents the breakthroughs, applications and latest research innovations of GANs and of quantum GANs. In particular, the book includes contributions on Autoencoders and Variational Autoencoders, Semi-Supervised GANs, Quantum GANs and Quantum Data Privacy, and Quantum GANs for image manipulation.
This book features selected research papers presented at the Third International Conference on Computing, Communications, and Cyber-Security (IC4S 2021), organized in Krishna Engineering College (KEC), Ghaziabad, India, along with Academic Associates; Southern Federal University, Russia; IAC Educational, India; and ITS Mohan Nagar, Ghaziabad, India, during October 30–31, 2021. It includes innovative work from researchers, leading innovators, and professionals in the area of communication and network technologies, advanced computing technologies, data analytics and intelligent learning, the latest electrical and electronics trends, and security and privacy issues.
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