AI Security Engineering: Design, Build, and Secure Dependable AI Systems: Design, Build, and Secure Dependable AI Systems - Tapa blanda

Sinopsis

Design, Build, and Secure Dependable AI Systems Across the Enterprise Lifecycle

AI is rapidly becoming part of core enterprise systems but most security programs were not designed for systems that are probabilistic, adaptive, and increasingly autonomous. AI Security Engineering provides a foundational, engineering-first playbook for designing, operating, and scaling secure AI systems across the enterprise lifecycle.

Written by Ashish Rajan, a CISO advising Fortune 500 organizations on AI security, this book focuses on security for AI systems not AI used as a security tool. It examines how AI changes traditional security assumptions and how organizations must adapt their architectures, pipelines, governance models, and operating practices to manage AI risk effectively in production environments.

Rather than focusing on tools or point solutions, AI Security Engineering applies security engineering principles to modern AI systems. It covers AI threat models, secure AI pipelines, runtime detection and incident response, governance and compliance at scale, and the emerging challenges of agentic and multi-model systems. Readers are guided through how to evolve existing security programs to support AI-enabled applications without slowing delivery or becoming the “department of no”.

This book shows how to:

• Design and operate secure AI systems across their full lifecycle from architecture and delivery to operations and scale
• Defend production AI applications against adversarial, emergent, and agent-driven threats
• Embed governance and risk controls into AI pipelines using engineering-first approaches
• Operate AI security in dynamic environments, including third-party and agentic systems
• Balance regulatory compliance, system performance, and engineering velocity

CISOs seeking strategic clarity for AI security investments, security architects designing resilient systems, and engineers responsible for operating AI in production will find this book a durable reference for building dependable AI systems at enterprise scale.

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