Use Cases

This section provides real-world use cases demonstrating how to implement security and compliance for AI workloads on IBM Cloud.

Regulatory-Ready GenAI Assistants

LLM-powered assistants with toxicity, IP, and PII filters, prompt-injection firewalls, and watsonx.governance monitoring. SCC WP secures the platform stack and provides evidence of compliance for audits.

Key Features

  • Toxicity detection and content filtering
  • Intellectual property and copyright protection
  • PII redaction and data privacy controls
  • Prompt injection and jailbreak defenses
  • Continuous monitoring and audit trails

Implementation

Deploy watsonx.governance for input/output guardrails, integrate SCC Workload Protection for runtime security, and configure automated evidence collection for regulatory compliance.

Healthcare Diagnostics (PHI)

Protected PHI pipelines with encryption and TEEs, explainability and model factsheets for clinicians, runtime safeguards against data leakage, and audit trails for HIPAA and ISO 42001 alignment.

Key Features

  • Protected Health Information (PHI) encryption at rest, in transit, and in use
  • Trusted Execution Environments (TEEs) for sensitive data processing
  • Model explainability and factsheets for clinical validation
  • Data leakage prevention and egress controls
  • HIPAA and ISO 42001 compliance evidence

Implementation

Enable confidential computing with IBM Hyper Protect or Intel SGX/TDX, deploy watsonx.governance for model documentation and explainability, and configure SCC Workload Protection for continuous compliance monitoring.

Financial Crime and Fraud Detection

High-throughput anomaly detection with hardened model APIs, rate limiting, and extraction defenses. SCC WP correlates risks across posture, identity, and runtime to prioritize remediation.

Key Features

  • Real-time anomaly detection and fraud prevention
  • Hardened model APIs with rate limiting
  • Model extraction and inversion defenses
  • Risk correlation across security domains
  • Prioritized remediation workflows

Implementation

Deploy models with secured endpoints and rate limiting, implement watermarking and fingerprinting for model protection, and use SCC Workload Protection for unified risk visibility and response.

Enterprise LLM Agents

Tool-enabled agents constrained by policy with scoped credentials and action whitelisting. Guardrails prevent unsafe actions and limit blast radius with continuous red teaming.

Key Features

  • Policy-constrained tool access and action whitelisting
  • Scoped credentials with least privilege access
  • Guardrails for unsafe action prevention
  • Blast radius limitation
  • Continuous red teaming and security testing

Implementation

Configure policy-as-code for agent actions, implement CIEM for credential management, deploy guardrails for action validation, and establish continuous red teaming processes.

Government and Critical Infrastructure

Zero-trust architectures with confidential computing for sensitive inference, Satellite for sovereign deployments, and continuous compliance with evidence generation.

Key Features

  • Zero-trust security architecture
  • Confidential computing for sensitive workloads
  • Sovereign deployment options with IBM Cloud Satellite
  • Data residency and sovereignty controls
  • Continuous compliance monitoring and evidence generation

Implementation

Deploy IBM Cloud Satellite for sovereign infrastructure, enable confidential computing for sensitive inference workloads, implement zero-trust network segmentation, and configure automated compliance evidence collection.

Getting Started

To implement these use cases:

  1. Run an AI security and compliance assessment
  2. Stand up a pilot with policy-as-code and guardrails
  3. Implement continuous assurance with automated evidence collection

Next Steps