Format
Häftad
Sidor
400 sidor
Språk
Engelska
Utgiven
mars 2026
Jämför priser
Från 263 kr263 kr
267 kr
349 kr
Priserna uppdateras löpande från säkra och trygga butiker.
Om boken
Use AI to Predict, Prevent, and Protect Against the Next Cyber Attack From cybersecurity leader Omar Santos and AI expert Dr. Petar Radanliev comes a groundbreaking guide to the future of cyber defense. This book is a practical guide to building intelligent, AI-powered cyber defenses in today’s fast-evolving threat landscape. With cyber threats growing in speed, scale, and sophistication, traditional defenses can no longer keep up. This essential book shows how to use AI technologies to detect threats earlier, respond faster and build stronger digital resilience. Designed for IT professionals, security analysts, engineers, executives, academics, and students, this guide bridges the gap between advanced AI technologies and real-world cybersecurity strategies. Whether you are managing enterprise networks, leading a security team, or preparing for a career in digital defense, this book will help you use AI to protect your most valuable assets. As ransomware attacks, data breaches, and zero-day exploits rise, organizations must move from reactive defense to proactive resilience. This book explains how technologies such as generative AI, large language models (LLMs), and small language models (SLMs) enable real-time threat detection, automated incident response, and predictive threat analysis. This book delivers:
- Clear explanations of AI technologies such as large language models (LLMs), generative AI, and behavior-based analytics.
- Hands-on strategies for leveraging AI to boost detection, response, recovery, and resilience.
- Case studies and practical tools to help you apply cutting-edge defense methods in real-world environments.
- Understand the fundamentals of digital cyber resilience in an AI-driven world and why traditional security methods are no longer enough.
- Gain deep insight into generative AI, large language models (LLMs), small language models (SLMs), and how they are transforming cybersecurity.
- Apply AI-based techniques for real-time threat detection, anomaly detection, and predictive threat forecasting.
- Implement AI-driven incident response strategies, including automated orchestration and real-time decision-making.
- Secure IoT devices and cloud infrastructures using machine learning, behavioral analytics, and AI-powered access control.
- Use advanced encryption, data privacy tools, and compliance frameworks powered by intelligent automation.
- Build and enhance cybersecurity programs and policies with AI integration for better governance and risk management.
- Ensure secure and ethical AI deployments, including continuous model updates and protection against adversarial attacks.
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