Cindy Green-Ortiz – författare
405 kr
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Today's organizations need a new security model that more effectively adapts to the complexity and risks of modern environments, embraces hybrid workplaces, and protects people, devices, apps, and data wherever they're located. Zero Trust is the first model with the potential to do all that. Zero Trust Architecture: Theory, Implementation, Maintenance, and Growth is the first comprehensive guide for architects, engineers, and other technical professionals who want to move from Zero Trust theory to implementation and successful ongoing operation.
A team of Cisco's leading experts and implementers offer the most comprehensive and substantive guide to Zero Trust, bringing clarity, vision, practical definitions, and real-world expertise to a space that's been overwhelmed with hype. The authors explain why Zero Trust identity-based models can enable greater flexibility, simpler operations, intuitive context in the implementation and management of least privilege security. Then, building on Cisco's own model, they systematically illuminate methodologies, supporting technologies, and integrations required on the journey to any Zero Trust identity-based model.
Through real world experiences and case study examples, you'll learn what questions to ask, how to start planning, what exists today, what solution components still must emerge and evolve, and how to drive value in the short-term as you execute on your journey towards Zero Trust.
- Nyhet
432 kr
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Securing AI Using Zero Trust Principles
Strategic Guidance for Defending AI Systems in a Rapidly Evolving Threat Landscape
Artificial intelligence is reshaping industries, driving innovation in critical sectors such as healthcare, finance, energy, and government. Yet, as organizations integrate AI into business operations, they inherit new risks, many of which conventional security models fail to address. Adversaries are weaponizing AI to automate reconnaissance, bypass defenses, and exploit vulnerable systems. The solution is not more trust, but less.
Zero Trust offers a foundational paradigm shift: no identity, device, system, or interaction is inherently trusted. Security must be continuously enforced, context-aware, and resilient by design. This book demonstrates how Zero Trust, when strategically applied to AI environments, enables organizations to secure data pipelines, mitigate emergent threats, and maintain control over evolving digital ecosystems.
Key insights include
AI Through a Security Lens: Demystifies machine learning, generative AI, and large language models with a focus on operational and business impact. Zero Trust Foundations: Provides a historical and architectural overview of Zero Trust, including Cisco’s Five Zero Trust Categories. Security by Design for AI: Offers guidance on protecting AI development workflows, from data ingestion and model training to inference and deployment. Threat Mitigation Strategies: Addresses adversarial AI, data poisoning, shadow AI, and insider misuse through identity enforcement, segmentation, and telemetry. Strategic Execution: Maps Zero Trust principles to regulatory frameworks including NIST AI RMF, EU AI Act, DORA, and ISO 27001, and provides actionable templates for running successful Zero Trust Segmentation Workshops.Who Should Read This Book:
CISOs and security architects building AI-resilient architectures AI and data leaders embedding AI into enterprise infrastructure Risk, compliance, and governance professionals navigating regulatory change Technical teams seeking secure-by-design methodologies for AI initiativesWhy This Matters Now:
AI systems are expanding faster than most organizations can govern them. The risks, ranging from operational disruption to model corruption, require proactive, architectural defenses. This book bridges the gap between AI innovation and trusted enterprise security.
Securing AI Using Zero Trust Principles delivers the strategic playbook for building resilient, trustworthy, and standards-aligned AI systems that can withstand the threats of today and tomorrow.