Secure AI Operations: Ensuring Integrated NVIDIA AI Security at Scale
Learn how modern security operations are evolving with the help of large language models (LLMs). By transforming reactive defenses into proactive strategies, you can enhance your organization's threat detection, streamline incident response and drive continuous improvement across the cybersecurity lifecycle.
WWT's AI Readiness Model for Operational Resilience (ARMOR) framework
World Wide Technology's AI Readiness Model for Operational Resilience (ARMOR) is a practical framework for securing AI and high-performance computing environments. ARMOR is built on real-world expertise and addresses the most urgent security challenges organizations face today. The framework is organized into different domains, each offering actionable guidance and maturity models for organizations at any stage of their AI journey:
- AI Governance, Risk and Compliance
- Secure AI Operations
- Model Protection
- Software Development Lifecycle (SDLC)
- Infrastructure Security
- Data Protection
- Cyber Resilience
Each domain is authored by subject matter experts and provides practical, vendor-agnostic insights for building resilient, compliant and innovative AI ecosystems.
Secure AI operations: What you'll find inside
This section focuses on transforming security operations for AI and HPC environments. ARMOR's secure AI operations guidance addresses the challenges of modern cyber threats, alert fatigue and the need for rapid, intelligent response—leveraging the power of large language models (LLMs) and automation to drive efficiency, resilience and continuous improvement.
Key principles and strategies
- Prevention: Move beyond reactive defenses with proactive, adaptive security policies, strong authentication and intelligent automation.
- Detection: Use AI-driven analytics and LLMs to identify threats faster, reduce false positives and gain deeper insights into security events.
- Response: Automate incident response, leverage contextual intelligence, and streamline investigations to minimize damage and recovery time.
- Recovery: Accelerate post-incident restoration with AI-powered playbooks, automated data restoration and compliance automation.
- Continuous improvement: Foster a culture of ongoing learning, review, and optimization—using LLMs to automate analysis, provide actionable insights and enhance decision-making.
Maturity model
ARMOR provides a Security Operations Maturity Model (SOMM) to help organizations benchmark their current capabilities and chart a path from reactive, manual processes to integrated, proactive, and adaptive security operations. The model encompasses people, processes and technology, highlighting the transformative impact of LLMs and automation at each stage.
Relevant frameworks and standards
ARMOR aligns with leading frameworks such as the CIS Critical Security Controls, NIST 800-61, ISO/IEC 27001 and more. The guidance supports compliance with industry regulations and best practices for security operations, incident response and business continuity.
Who should read this and why
This section is for security operations leaders, SOC managers, incident responders, and anyone responsible for protecting AI and HPC environments from evolving cyber threats. If your organization is struggling with alert overload, manual processes, or the complexity of modern attacks, the Secure AI Operations domain provides practical insights and actionable steps to modernize your security operations.
Why keep reading
- Learn how to leverage LLMs and automation to transform security operations
- Find best practices for prevention, detection, response, recovery and continuous improvement
- Benchmark your organization's maturity and identify steps for improvement
- Build confidence that your security operations are robust, scalable and ready for the future
Unlock the full report for in-depth guidance, implementation approaches, and expert insights to help you build a resilient, efficient and adaptive security operations program for AI and HPC environments.
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