Securing Smart Cities With Quantum-Enhanced Deep Learning
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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.
Sarveshwaran, Velliangiri: - 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.
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