Intrusion Detection
Monitoring AI infrastructure and applications for malicious activity or policy violations, triggering alerts or automated responses.
Definition
Extends traditional cybersecurity to AI-specific threats—model inversion, API abuse, unusual inference patterns. Governance includes deploying IDS/IPS systems that analyze logs, network traffic, and model-usage metrics; defining incident-response playbooks; and conducting regular penetration tests to validate detection effectiveness.
Real-World Example
A cloud-based ML service integrates an IDS that watches for anomalous patterns—such as large volumes of inference requests from a single IP (potential model extraction). When thresholds are exceeded, it automatically throttles the traffic and notifies the security team for investigation.
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