AI SCADA Security Analytics
The Problem
“Detect SCADA cyber threats before outages occur”
Organizations face these key challenges:
High-volume SCADA/ICS telemetry with limited context overwhelms analysts, causing alert fatigue and missed early indicators
Signature/rule-based detection fails against novel threats, living-off-the-land activity, and misuse of legitimate engineering tools
OT constraints (legacy devices, uptime requirements, vendor diversity) limit patching and instrumentation, making continuous monitoring difficult
Impact When Solved
The Shift
Human Does
- •Review SCADA, network, and access logs to identify suspicious activity
- •Correlate OT alarms with IT security events and plant operating context
- •Triage alerts, investigate incidents, and decide containment actions
- •Collect audit evidence and prepare compliance reporting for control reviews
Automation
- •Apply static rules and signature checks to known threat indicators
- •Trigger threshold-based alarms from predefined SCADA and network conditions
- •Aggregate monitoring outputs into basic alert queues for analyst review
Human Does
- •Approve response actions for high-risk control anomalies and suspected intrusions
- •Review prioritized incidents and decide escalation, containment, or recovery steps
- •Handle exceptions involving safety, uptime, or ambiguous operating conditions
AI Handles
- •Continuously monitor OT and IT telemetry to learn normal asset and site behavior
- •Detect anomalous commands, process changes, access activity, and lateral movement
- •Correlate multi-source events and risk-score alerts to reduce false positives
- •Generate investigation summaries, audit-ready evidence, and recommended next actions
Operating Intelligence
How AI SCADA Security Analytics runs once it is live
AI surfaces what is hidden in the data.
Humans do the substantive investigation.
Closed cases sharpen future detection.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Scan
Step 2
Detect
Step 3
Assemble Evidence
Step 4
Investigate
Step 5
Act
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI scans and assembles evidence autonomously. Humans do the substantive investigation. Closed cases improve future scanning.
The Loop
6 steps
Scan
Scan broad data sources continuously.
Detect
Surface anomalies, links, or emerging signals.
Assemble Evidence
Pull related records into a working case file.
Investigate
Humans interpret evidence and make case judgments.
Authority gates · 1
The system must not approve or execute high-risk control actions without review and direction from a control-room operator or other designated human authority.[S1]
Why this step is human
Investigative judgment involves ambiguity, legal considerations, and stakeholder impact that require human expertise.
Act
Carry out the human-directed next step.
Feedback
Closed investigations improve future detection.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in AI SCADA Security Analytics implementations:
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