Ai - Securing Industrial Control Systems

Harness AI for Threat Detection, Anomaly Monitoring, and Cyber Defense in ICS and OT Environments

What you'll learn

Learners will be able to identify and analyze modern cyber threats targeting ICS/OT environment, including those augmented by artificial intelligence (AI)

Learners will show how AI enhances ICS/OT threat detection, anomaly detection, access control, and real-time/predictive response strategies.

Learners will analyze AI exploits in industry and propose mitigations like input validation, prompt filtering, and human-in-the-loop oversight.

Learners will design AI-enabled OT security architectures focused on safety, explainability, and resilience against AI-driven attacks.

Requirements

This course is designed for security professionals, engineers, and decision-makers. While AI is covered in-depth, the focus is conceptual and applied, not on coding models from scratch.

Description

This course explores how artificial intelligence (AI) is revolutionizing cybersecurity for industrial control systems (ICS) and operational technology (OT) environments. It is designed for college and university students, engineers, cybersecurity professionals, and both IT and OT practitioners ready to integrate AI into protecting critical infrastructure. Learners start with AI fundamentals—covering supervised, unsupervised, and reinforcement learning—before advancing to practical, real-world applications such as threat detection, anomaly monitoring, predictive maintenance, and automated incident response. The course offers actionable strategies for deploying AI securely across ICS/OT ecosystems. It includes guidance on designing layered security architectures, building AI-enabled detection pipelines, and implementing explainable and auditable models. Learners will grasp deployment considerations for edge, centralized, hybrid, and federated AI systems while understanding how to align architecture with industry standards like IEC 62443 and NIST’s AI Risk Management Framework. Real-world case studies from the automotive, power, water treatment, oil & gas (upstream, midstream, and downstream), and manufacturing sectors illustrate how both defenders and adversaries utilize AI. Learners will also delve into risk mitigation, prompt injection, adversarial machine learning, and human-in-the-loop governance. By the end of the course, students will be equipped with the skills, frameworks, and insights needed to safely and effectively apply AI to protect industrial control systems and operational technology.

Overview

Section 1: Introduction to AI in ICS and OT Security

Lecture 1 Introduction to AI in ICS and OT Security

Section 2: AI Fundamentals for ICS and OT

Lecture 2 AI Fundamentals for ICS and OT

Section 3: Understanding Threat Detection with AI

Lecture 3 Understanding Threat Detection with AI

Section 4: Integrating AI into Industrial Environments

Lecture 4 Integrating AI into Industrial Environments

Section 5: AI for Predictive Maintenance in ICS and OT

Lecture 5 AI for Predictive Maintenance in ICS and OT

Section 6: Lesson 6 - Future Trends Compliance and Responsible AI in ICS and OT

Lecture 6 Future Trends Compliance and Responsible AI in ICS and OT

Section 7: AI Risk Assessment and Governance in ICS and OT

Lecture 7 AI Risk Assessment and Governance in ICS and OT

Section 8: Understanding AI Implementation Risks

Lecture 8 Understanding AI Implementation Risks

Section 9: AI Vulnerabilities Hallucination Deception and Exploits

Lecture 9 AI Vulnerabilities Hallucination Deception and Exploits

Section 10: Cyber Defense Threat Hunting with AI

Lecture 10 Cyber Defense Threat Hunting with AI

Section 11: Building AI Driven OT Security Architectures

Lecture 11 Building AI Driven OT Security Architectures

Section 12: Cyber Attacks and AI Exploits on ICS and OT Systems

Lecture 12 Cyber Attacks and AI Exploits on ICS and OT Systems

This course is designed for professionals working in or transitioning into industrial cybersecurity roles who want to understand how artificial intelligence (AI) can be applied to secure operational technology (OT) and industrial control systems (ICS). No prior AI programming knowledge is required, but a basic understanding of ICS/OT environments and cybersecurity principles is recommended for maximum value.