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Inhaltsangabe
As urban environments become interconnected through smart infrastructure, the need for advanced security mechanisms has grown. Smart cities rely on sensors, communication systems, and intelligent devices to manage transportation, energy distribution, public safety, healthcare, and other critical services. However, the growing complexity and scale of these systems also exposes them to cyber threats and data vulnerabilities. Quantum-enhanced deep learning strengthens smart city security by combining the computational power of quantum technologies with the adaptive intelligence of deep neural networks. This integration enables faster threat detection, improved pattern recognition, secure data processing, and more efficient decision-making in urban environments. By leveraging quantum computing principles alongside advanced AI models, future smart cities may achieve higher levels of resilience, privacy, and cybersecurity against evolving digital attacks. Securing Smart Cities With Quantum-Enhanced Deep Learning examines how AI, deep learning, and quantum computing shape the future of cybersecurity and smart ecosystems. It explores AI-powered intrusion detection, anomaly detection, cyber resilience strategies, quantum-enhanced learning, and post-quantum cryptography for securing next-generation ecosystems. This book covers topics such as federated learning, edge computing, and transportation systems, and is a useful resource for engineers, security professionals, urban developers, academicians, researchers, and scientists.
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Über die Autorinnen und Autoren
Velliangiri Sarveshwaran earned his Bachelor’s degree in Computer Science and Engineering from Anna University, Chennai, and completed his Master's in Computer Science and Engineering at Karpagam University, Coimbatore, followed by a Doctor of Philosophy in Information and Communication Engineering from Anna University, Chennai. Presently, he holds the position of Post-Doctoral Research Fellow in the Department of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. He is a senior member of both the Institute of Electrical and Electronics Engineers (IEEE) and the International Association of Engineers (IAENG). Dr. Velliangiri conducts reviews for IEEE Transactions, Elsevier, Springer, Inderscience, and other reputable Scopus-indexed journals, specializing in Blockchain, Security and Privacy and Optimization techniques. With over 50 publications in SCI Indexed journals and presentations at more than 30 International conferences, he is actively engaged as a technical program committee member and conference chair at numerous international events. Furthermore, Dr. Sarveshwaran has edited and authored books published by esteemed publishers such as Elsevier, Springer, River, and CRC Press Publishers. He serves as the series editor of “Artificial Intelligence for Sustainability” at CRC Press, Taylor and Francis Group, in addition to holding positions as Area Editor at the EAI Endorsed Journal of Energy (Scopus) and Academic Editor at the Journal of Wireless Communication and Mobile Computing (Scopus, SCI) with Hindawi Publishers. His significant contributions to the field were recognized by Stanford University in 2023, where he was ranked in the Top 2% of Scientists globally in the field of “Artificial Intelligence & Image Processing, Information & Communication Technology” based on his research publications in this domain.
Priyanka Verma serves as Programme Director and Assistant Professor in the School of Computer Science at the University of Galway, Ireland, where she leads €1M+ funded research projects. Previously, she worked as a a Research Fellow in the Department of Electronics and Computer Engineering at the University of Limerick. She is working on the Science Foundation of Ireland (SFI) funded National Challenge Fund Project Cyber-Shock, focusing on advancing research in cybersecurity. Dr Priyanka also held the position of Prestigious Marie Curie Research Fellow in Data Science Institute at University of Galway. Funded by the European Union and SFI under the competitive SMART 4.0 Marie Sklodowska-Curie Action, she received €194,329.00 in funding for her project Secure-ACT. With over 14 years of teaching & research experience in computer science, Priyanka has made significant contributions to academia. She served as an Assistant Professor at MANIT, teaching undergraduate and postgraduate programs. During her PhD, she also held a teaching assistant role at ABV-IIITM in India. Priyanka’s scholarly impact extends beyond academia, with numerous publications in esteemed journals in IEEE/ACM/Elsevier and top conferences. She is a Senior Member of IEEE, holds a Fellow position with IETE, and is a Professional Member of ACM. She is recognized as a Young Scientist by the MPCST, India, and has received prestigious awards such as the SRIJAN for excellence in teaching and PHDCCI Young Researcher for the exceptional research work, highlighting her remarkable contributions to cybersecurity and Artificial Intelligence. Furthermore, Priyanka undertook the MIT Professional Education in Leadership & Innovation in 2022. She is also a co-founder of the Active Foundation established in 2015. Originally from Bhopal, India and presently resides in Galway and loves to enjoys exploring various countries throughout Europe. Priyanka is also keenly interested in diverse cultures as well as world history.
Por Lip Yee is a Professor at the Faculty of Computer Science & Information Technology, Universiti Malaya, specializes in cybersecurity, IoT, and AI. He leads the IoT Research Group and contributes to SECREG, focusing on AI-driven solutions for biomedical, cybersecurity, and IoT challenges. As a dedicated educator and researcher, he actively collaborates on impactful global projects.
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Securing Smart Cities With Quantum-Enhanced Deep Learning (Paperback)
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Paperback. Zustand: new. Paperback. As urban environments become interconnected through smart infrastructure, the need for advanced security mechanisms has grown. Smart cities rely on sensors, communication systems, and intelligent devices to manage transportation, energy distribution, public safety, healthcare, and other critical services. However, the growing complexity and scale of these systems also exposes them to cyber threats and data vulnerabilities. Quantum-enhanced deep learning strengthens smart city security by combining the computational power of quantum technologies with the adaptive intelligence of deep neural networks. This integration enables faster threat detection, improved pattern recognition, secure data processing, and more efficient decision-making in urban environments. By leveraging quantum computing principles alongside advanced AI models, future smart cities may achieve higher levels of resilience, privacy, and cybersecurity against evolving digital attacks. Securing Smart Cities With Quantum-Enhanced Deep Learning examines how AI, deep learning, and quantum computing shape the future of cybersecurity and smart ecosystems. It explores AI-powered intrusion detection, anomaly detection, cyber resilience strategies, quantum-enhanced learning, and post-quantum cryptography for securing next-generation ecosystems. This book covers topics such as federated learning, edge computing, and transportation systems, and is a useful resource for engineers, security professionals, urban developers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798337374895
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Securing Smart Cities With Quantum-Enhanced Deep Learning (Paperback)
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Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: new. Paperback. As urban environments become interconnected through smart infrastructure, the need for advanced security mechanisms has grown. Smart cities rely on sensors, communication systems, and intelligent devices to manage transportation, energy distribution, public safety, healthcare, and other critical services. However, the growing complexity and scale of these systems also exposes them to cyber threats and data vulnerabilities. Quantum-enhanced deep learning strengthens smart city security by combining the computational power of quantum technologies with the adaptive intelligence of deep neural networks. This integration enables faster threat detection, improved pattern recognition, secure data processing, and more efficient decision-making in urban environments. By leveraging quantum computing principles alongside advanced AI models, future smart cities may achieve higher levels of resilience, privacy, and cybersecurity against evolving digital attacks. Securing Smart Cities With Quantum-Enhanced Deep Learning examines how AI, deep learning, and quantum computing shape the future of cybersecurity and smart ecosystems. It explores AI-powered intrusion detection, anomaly detection, cyber resilience strategies, quantum-enhanced learning, and post-quantum cryptography for securing next-generation ecosystems. This book covers topics such as federated learning, edge computing, and transportation systems, and is a useful resource for engineers, security professionals, urban developers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798337374895
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