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portada Data–Driven Network Intelligence for Cyber Security (Wiley – Ieee) (en Inglés)
Formato
Libro Físico
Año
2022
Idioma
Inglés
N° páginas
250
Encuadernación
Tapa Dura
Dimensiones
22.9 x 15.2 x 1.0 cm
Peso
0.37 kg.
ISBN13
9781119783916

Data–Driven Network Intelligence for Cyber Security (Wiley – Ieee) (en Inglés)

Yi Qian (Autor) · Shengjie Xu (Autor) · Rose Qingyang Hu (Autor) · Wiley-IEEE Press · Tapa Dura

Data–Driven Network Intelligence for Cyber Security (Wiley – Ieee) (en Inglés) - Xu, Shengjie ; Qian, Yi ; Hu, Rose Qingyang

Libro Físico

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Origen: Estados Unidos (Costos de importación incluídos en el precio)
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Reseña del libro "Data–Driven Network Intelligence for Cyber Security (Wiley – Ieee) (en Inglés)"

CYBERSECURITY IN INTELLIGENT NETWORKING SYSTEMS Help 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 threats Latest technologies in data-driven privacy preservation, including differential privacy, federated learning, and homomorphic encryption Key areas in adversarial machine learning, from both offense and defense perspectives Descriptions of network anomalies and cyber threats Background information on data-driven network intelligence for cybersecurity Robust and secure edge intelligence for network anomaly detection against cyber intrusions Detailed descriptions of the design of privacy-preserving security protocols Cybersecurity in Intelligent Networking Systems is an essential reference for all professional computer engineers and researchers in cybersecurity and artificial intelligence, as well as graduate students in these fields.

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