Machine learning deep security (13 Ergebnisse)

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Neuware - Unlock the future of cyber defense with Cyber Defense Intelligence. Dive into a world where AI innovations meet cybersecurity, offering the ultimate guide to safeguard against sophisticated threats. Transform your understanding and arm yourself with the best tools for the modern digital battlefield. Learn how real-time algorithms revolutionize threat detection, providing speed and precision previously thought impossible. This book brings the complexities of AI cybersecurity into focus, making them accessible whether you're just beginning or an industry expert looking to refine your skills further. Feel empowered as you grasp techniques in behavioral analysis and machine learning, crucial for preemptive threat identification. Understand the challenges and opportunities AI creates and equip yourself to build stronger, smarter security systems. Enhance your cybersecurity acumen and deliver unparalleled protection to your network. Ensure accuracy and efficacy in your threat detection systems. In Cyber Defense Intelligence, each chapter unfolds practical insights and actionable steps, designed to boost your AI integration from concept to execution. Elevate your strategies and develop a robust, adaptive defense framework. Additional benefits include exclusive case studies, practical implementation guides, and techniques to refine your approach to AI-driven solutions.» Master threat pattern recognition and disrupt future attacks before they occur» Leverage AI to amplify your cybersecurity barrier with effortless precision» Eliminate obsolete defenses and harness real-time AI advancements» Prevent costly breaches by optimizing detection accuracy with strategic insights>Written by an industry veteran with over 25 years of ICT experience, these pages hold the expertise and guidance from a seasoned professional who also offers consultation and training services.…

Buch. Zustand: Neu. Neuware - The topic of this book is the evolving landscape of cloud database security and its role in the threat of cyber-attacks by artificial intelligence (AI). It begins with the introduction of basic cloud computing concepts, points out the significant security problems, and describes data protection as important. The authors delve into deep learning (DL) and machine learning (ML) techniques for real-time threat detection, anomaly identification, and intrusion prevention. The book covers the use of AI for security mechanisms, predictive analytics, and automated threat intelligence sharing. It also discusses new developments, such as federated learning, blockchain security, and homomorphic encryption. In addition, the text deals with the risks of quantum computing, regulation compliance, and rising threats. The book is a standalone cybersecurity reference for students, professionals, and researchers based on acknowledged theoretical ideas and practical applications. Cloud security should include AI and ML to improve integrity and resilience against smart threats.…

Zustand: New.

Paperback. Zustand: Brand New. 346 pages. 10.00x7.00x10.00 inches. In Stock.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New.

Hardcover. Zustand: Brand New. 350 pages. 6.14x2.00x9.21 inches. In Stock.

Hardcover. Zustand: Brand New. 336 pages. 10.00x7.00x0.98 inches. In Stock.

Buch. Zustand: Neu. Neuware - We are living in an AI and data-driven era. A huge volume of data is generated from all sectors including smart cities, intelligent transportation systems, smart healthcare, education, smart agriculture and smart industrial processes. This information comprises multiple modalities such as textual data, images, sound, gestures and genetic sequences, which are generated through various sources. The internet of multimedia things (IoMT) is one of the key contributors to the collection, analysis and management of voluminous multimodal data. The dominating features of IoMTs are well-timed delivery of data and dependability, but they require high levels of memory and computational power, which requires higher bandwidth and more power. Therefore, they require rigorous quality of service (QoS) and efficient, reliable and secure network frameworks. The objective of this book is to explore machine learning (ML) and deep learning (DL) techniques for securing data with multiple modalities in a wide range of data-centric smart applications in the IoMT framework. In all data-centric application domains where on-time availability of data and reliability are the major concerns, IoMT is contributing significantly. The authors present the challenges faced to organize and process multimodal data in data-centric applications, several types of data modalities, and innovative IoMT frameworks. A particular focus is placed on the role of ML and DL techniques in securing multi-modal data for real-time monitoring in smart environment applications. Machine Learning and Deep Learning Driven Techniques for Multimodal Data Security in the Internet of Multimedia Things caters to the needs of AI, big data and IoT advanced students, academic and industry researchers, engineers, security experts, data analysts, and AI and data-centric application developers.…

Zustand: New. In English.

Zustand: New. In English.