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Deep Learning Innovations for Securing Critical Infrastructures

Name: Deep Learning Innovations for Securing Critical Infrastructures
Brand: IGI Global
SKU: 9798337305646
Price: 325.9 EUR
Availability: InStock

Автор: Sheng-Lung Peng, Parag Jain

Език:

Корици: С меки корици

Издател: IGI Global

Наличност: Външен склад

Изпращаме след 10-18 дни

325.90 € 637.40 лв

Deep learning innovations play a crucial role in securing critical infrastructures, offering advance...

Информация за книгата

Автор

Sheng-Lung Peng, Parag Jain

Език

Английски език

Корици

Книга - С меки корици

Издадена

2025

страници

646

EAN

9798337305646

Enbook ID

48491682

Издател

IGI Global

Теглоt

1474

Размери

216 x 279 x 33

Пълно описание

Deep learning innovations play a crucial role in securing critical infrastructures, offering advanced solutions to protect vital systems from sophisticated cyber threats. By leveraging neural networks and advanced algorithms, deep learning enables real-time anomaly detection, pattern recognition, and predictive threat analysis, which are essential for safeguarding critical sectors such as energy, transportation, healthcare, and finance. These technologies can identify vulnerabilities, respond to breaches, and adapt to new attacks, providing a strong defense against cyber risks. As the digital landscape becomes more interconnected, the integration of deep learning into cybersecurity strategies will enhance resilience while ensuring the safe operation of essential services. Deep Learning Innovations for Securing Critical Infrastructures explores the cutting-edge integration of neural networks and artificial intelligence (AI) in modern cybersecurity systems. It examines how AI, particularly neural network models, is revolutionizing cybersecurity by automating threat detection, analyzing complex data patterns, and implementing proactive defense mechanisms. This book covers topics such as blockchain, cloud computing, and event management, and is a useful resource for business owners, computer engineers, data scientists, academicians, and researchers.