Network Security
Measures and controls (e.g., segmentation, firewalls, intrusion detection) to protect AI infrastructure and data pipelines from unauthorized access or tampering.
Encompasses firewalls, VLANs, zero-trust segmentation, secure API gateways, and AI-specific defenses (model-extraction detection, encrypted inference). Governance involves network-access policies, regular penetration testing, automated security compliance scans, and integration of AI-infrastructure logs into SIEM platforms to detect and respond to threats in real time.
A cloud-hosted ML platform uses micro-segmentation to isolate training environments from production inference clusters, deploys web-application firewalls to protect model APIs, and feeds network logs into a SIEM system with rules to detect unusual data-exfiltration patterns - ensuring AI assets remain secure against cyber threats.
“What used to take weeks of manual reviews and policy work is now structured and auditable in Enzai within minutes. It’s the first time AI governance has felt operational, not theoretical.”
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