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(Ebook) Cybersecurity in Intelligent Networking Systems (IEEE Press) by Shengjie Xu, Yi Qian, Rose Qingyang Hu ISBN 9781119783916, 1119783917

  • SKU: EBN-47252652
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Instant download (eBook) Cybersecurity in Intelligent Networking Systems (IEEE Press) after payment.
Authors:Shengjie Xu, Yi Qian, Rose Qingyang Hu
Pages:144 pages.
Year:2022
Editon:1
Publisher:Wiley-IEEE Press
Language:english
File Size:10.1 MB
Format:rar
ISBNS:9781119783916, 1119783917
Categories: Ebooks

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(Ebook) Cybersecurity in Intelligent Networking Systems (IEEE Press) by Shengjie Xu, Yi Qian, Rose Qingyang Hu ISBN 9781119783916, 1119783917

CYBERSECURITY IN INTELLIGENT NETWORKING SYSTEMSHelp protect your network system with this important reference work on cybersecurity Cybersecurity and privacy are critical to modern network systems. As various malicious threats have been launched that target critical online services—such as e-commerce, e-health, social networks, and other major cyber applications—it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in protecting the security of modern network systems and ensuring information privacy. Cybersecurity in Intelligent Networking Systems provides a background introduction to data-driven cybersecurity, privacy preservation, and adversarial machine learning. It offers a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide robust and trustworthy safeguards with edge-enabled cyber infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing on encryption-based security protocol, this book also highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology. Cybersecurity in Intelligent Networking Systems readers will also find: Fundamentals in AI for cybersecurity, including artificial intelligence, machine learning, and security threatsLatest technologies in data-driven privacy preservation, including differential privacy, federated learning, and homomorphic encryptionKey areas in adversarial machine learning, from both offense and defense perspectivesDescriptions of network anomalies and cyber threatsBackground information on data-driven network intelligence for cybersecurityRobust and secure edge intelligence for network anomaly detection aga
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