Gibbs marcel (10 Ergebnisse)
Sprache: Englisch
Verlag: Independently Published, 2026
Serie: Buch 2 von 4 - The Practical AI Systems for Small Business Owners 2026 Series
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Independently Published, 2026
Serie: Buch 2 von 4 - The Practical AI Systems for Small Business Owners 2026 Series
- Softcover
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: PBShop.store US, Wood Dale, IL, USAPBShop.store US
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
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Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - What happens after your AI agents are deployed Most organizations focus on building, securing, testing, and governing agentic AI systems. Far fewer are prepared for the challenges that emerge when autonomous agents begin making decisions, invoking tools, accessing sensitive resources, and col…laborating with other agents in real production environments.How do you detect dangerous behavior before it causes damage How do you stop a compromised agent in real time How do you contain failures, enforce policies at runtime, and maintain control as autonomous systems operate at machine speed Practical Runtime Security and Defense for Agentic AI Systems provides a hands-on blueprint for continuously protecting autonomous AI agents and multi-agent systems after deployment. Designed for security engineers, AI platform teams, DevSecOps professionals, architects, and enterprise technology leaders, this book focuses on the operational security controls required to defend agentic AI systems in production.Rather than relying on theory, this book shows you how to implement practical runtime defense strategies, automated response mechanisms, behavioral monitoring pipelines, containment workflows, and self-healing security controls that work in modern enterprise environments.Inside, you will learn how to: - Build runtime security architectures for autonomous AI agents and multi-agent systems- Implement policy enforcement, guardrails, and real-time action controls- Establish behavioral monitoring and anomaly detection capabilities- Deploy automated containment, isolation, and kill-switch mechanisms- Create agent control towers and runtime observability pipelines- Design self-healing security workflows and autonomous defense systems- Investigate incidents using traceability, telemetry, and forensic analysis- Integrate runtime security into AgentOps, DevSecOps, and CI/CD pipelines- Strengthen operational resilience across cloud, hybrid, and multi-agent environments- Scale continuous protection strategies for enterprise AI platformsAs agentic AI systems become more capable, runtime security is rapidly becoming one of the most important disciplines in enterprise AI. Organizations need more than prevention, they need the ability to detect, respond, recover, and adapt while autonomous systems are actively operating.Whether you are securing a single AI agent or managing a large-scale multi-agent ecosystem, this book provides the practical architectures, implementation patterns, operational playbooks, and proven defense strategies needed to maintain control in production.If you are ready to move beyond static security controls and build resilient, continuously protected AI systems, this book will help you create the runtime defense capabilities modern enterprises require.Get your copy today and learn how to protect autonomous AI systems where it matters most, while they are running.
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - How do you secure an application that can rewrite its own execution logic at runtime As organizations rapidly deploy autonomous AI agents with direct write access to database engines, internal networks, and cloud infrastructure, traditional perimeter defense models fall short. When your softw…are moves from deterministic code to probabilistic reasoning loops, how do you stop an adversary from hijacking your entire enterprise platform Advanced Threat Modeling and Red Teaming for Agentic AI Systems provides the definitive, production-first blueprint to secure non-deterministic software deployments. This comprehensive technical guide skips basic introductory concepts to deliver hard-hitting offensive engineering strategies, automated vulnerability testing pipelines, and zero-trust defensive hardening patterns. It addresses the unique architectural realities of modern multi-agent systems, shifting your security posture from reactive prompt filtering to code-enforced, continuous validation across your entire cluster fabric.What advantages will you gain by engineering your security framework from the ground up This manual equips platform architects, security engineers, and DevSecOps teams with the exact technical skills required to build an automated, self-healing defensive lifecycle.By implementing the production-grade methodologies detailed inside, you will acquire the skills to: - Build stateful autonomous red team agents to programmatically simulate complex, multi-turn adversarial cascades.- Embed declarative automated fuzzing and prompt regression scanners directly into containerized CI/CD pipelines as mandatory release quality gates.- Inject semantic faults and behavioral noise to evaluate multi-agent swarm resilience and configure robust infrastructure circuit breakers.- Decouple tool execution privileges from volatile model logic using relationship-based access control models.- Harden human-in-the-loop approval interfaces against context-spoofing and parameter manipulation exploits.- Establish weighted risk quantification frameworks that translate probabilistic alignment flaws into deterministic business risk metrics.Do not wait for a critical semantic breach to expose your core infrastructure. Secure your autonomous workflows, harden your multi-agent networks, and enforce strict policy-as-code gates today.Buy your copy now to deploy production-grade defense validation across your enterprise platform.
- Softcover
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Taschenbuch. Zustand: Neu. Neuware - Deploying AI agents is no longer the hardest part.Keeping them governed, compliant, observable, and secure in production is.As organizations rapidly adopt autonomous agents, multi-agent systems, and AI-powered workflows, many discover that traditional governance and security models were never… designed for systems that can make decisions, invoke tools, access sensitive data, and collaborate with other agents autonomously.How do you enforce policies at runtime How do you maintain continuous compliance across thousands of agent actions How do you create audit trails that satisfy regulators, security teams, and enterprise stakeholders How do you detect and contain risky agent behavior before it becomes a business problem Practical Agentic AI Governance, Compliance, and Runtime Security provides a hands-on blueprint for building governance and runtime protection capabilities that work in real-world enterprise environments.Rather than focusing on theory, this book shows you how to implement governance controls, compliance automation, runtime policy enforcement, observability pipelines, audit frameworks, and operational security mechanisms that can scale across modern AI platforms.Inside, you will learn how to: - Build governance control planes for autonomous agents and multi-agent systems- Implement policy-as-code using modern authorization and policy frameworks- Establish continuous compliance programs aligned with leading industry standards- Create immutable audit trails and enterprise-grade traceability pipelines- Deploy runtime guardrails and enforcement mechanisms for agent actions- Monitor agent behavior and detect anomalies in real time- Integrate governance and compliance controls into CI/CD workflows- Automate evidence collection, reporting, and audit preparation- Build incident response and recovery procedures for agent-driven environments- Scale governance programs across cloud, hybrid, and multi-tenant architecturesWhether you are a security engineer, AI platform architect, DevSecOps professional, governance specialist, or technology leader, this book provides practical guidance, implementation patterns, operational playbooks, and proven architectures for governing agentic AI systems at enterprise scale.If your organization is building the next generation of autonomous AI systems, this book will help you move beyond deployment and establish the governance, compliance, and runtime security foundations required for long-term success.Build systems that are not only intelligent, but also auditable, compliant, trustworthy, and continuously protected.
