The integration of generative AI in industrial networking is reshaping how security frameworks, such as IEC 62443, are implemented and maintained. By automating threat detection, network configurations and compliance monitoring, AI-driven programming is a powerful tool to shorten the gap between the security challenges in operational technology (OT).
Generative AI insights
- Generative AI is a branch of artificial intelligence that can create, generate code and predict patterns.
- Generative AI is evolving and plays an important role in industrial networking.
- Security remains a challenge for generative AI in industrial networking.
Industrial networks form the backbone of critical infrastructure, supporting sectors like energy, manufacturing and transportation. However, with the increasing convergence of information technology (IT) and operational technology (OT), cybersecurity threats are growing at an alarming rate. The International Society of Automation/International Electrotechnical Commission (ISA/IEC) 62443 standard provides a structured approach to securing industrial automation and control systems (IACS), but security adoption requires constant monitoring, configuration and adaptation.
Generative AI — an advanced branch of artificial intelligence that can create content, generate code and predict patterns — has emerged as a powerful tool in supporting different solutions to address these challenges. In industrial networking, AI-driven programming opens a new horizon, transforming cybersecurity by supporting and automating some processes of threat detection, enhancing anomaly detection and ensuring compliance with stringent security frameworks like ISA/IEC 62443.
What is generative AI?
Before we can understand generative AI’s role in industrial networking, it’s important to define the technology.
Generative AI a type of artificial intelligence that can create new content. The technology works by generating new data from existing data and reusing existing knowledge to solve new queries.
This technology is most used in chatbots, product development and media creation.
The role of generative AI in industrial networking
Generative AI is revolutionizing industrial networking by enabling:
- Automated network configuration and optimization
AI can generate optimized network configurations that align with IEC 62443 security zones and conduits, reducing human error and improving efficiency.
- Threat detection and response
AI models can analyze large datasets in real time, identifying anomalies and generating insights to respond to actions that mitigate security risks.
- Self-healing networks
AI-powered systems can detect communication failures, generate remediation scripts and provide automated insights to reduce downtime and improve current configurations.
- Compliance and audit automation
Generative AI can generate security documentation, verify configurations against IEC 62443 requirements and assist in auditing processes.
Two ways IEC 62443 and AI enhance cybersecurity compliance
IEC 62443 provides a framework for securing industrial automation systems by defining security levels (SLs), access controls and risk assessment methodologies. AI-driven programming enhances compliance in the following ways:
- Risk identification and threat modeling
AI can generate threat models based on historical attack patterns and predict the most likely vulnerabilities considering the specifics of each network. While visibility tools remain important, companies can perform additional analysis to feed their internal know-how and double-check the identified patterns.
2. Security Patch Management
AI can suggest patches dynamically, ensuring that maintenance teams are more actively looking into system vulnerabilities.
Ways Generative AI enhances industrial control systems (ICS) security
Generative AI goes beyond enhancing cybersecurity compliance and enhances industrial control systems (ICS). There are two significant ways in which generative AI accomplish this:
AI-Assisted Network Configuration for Secure Zones and Conduits
In industrial networks, defining security zones and conduits per IEC 62443 is crucial. Generative AI can:
- Analyze network traffic to recommend specific AI models (mathematical models) that are best suited to respond and suggest optimal security segmentation based on network data patterns.
- Propose firewall rules and access control lists.
- Simulate potential attack vectors and recommend network hardening strategies.
Intelligent Intrusion Detection and Incident Response
Traditional IDS (Intrusion Detection Systems) rely on signature-based detection, which often fails against zero-day attacks. Generative AI improves this by:
- Analyzing real-time network traffic and providing additional insights to detection tools to identify behavioral anomalies.
- Supporting the creation of response playbooks tailored to the nature of the threat and ICS characteristics.
- Simulating potential attack paths and recommending insight for mitigation strategies.
AI-Powered Compliance Auditing and Reporting
IEC 62443 compliance involves detailed documentation and continuous auditing. AI can:
- Support the creation of compliance documentation based on real-time network data.
- Analyze logs for deviations from IEC 62443 guidelines.
- Recommend remediation actions to address compliance gaps proactively.
Generative AI has some challenges and considerations
While generative AI offers significant benefits, its adoption in industrial networking must address key challenges:
- Explainability and trust: AI-generated security policies and configurations must be transparent and understandable for operators.
- Integration with legacy systems: Many industrial environments rely on outdated infrastructure that may not support AI-driven automation.
- Cybersecurity risks of AI itself: AI models can become targets for adversarial attacks, requiring additional security measures.
- Decision-making in industrial control systems: AI should not make automated decisions on Industrial Control Systems but instead offer powerful insights to the asset owner, increasing response time and digitizing large quantities of data to facilitate human decision-making.
Generative AI continues to evolve
Generative AI has the potential to transform cybersecurity in industrial networking by automating complex tasks, improving IEC 62443 compliance and reducing response times to cyber threats. As AI-powered programming continues to evolve organizations must strike a balance between automation and human oversight to ensure secure and resilient industrial networks.
By leveraging generative AI, industrial enterprises can move toward a future where cybersecurity is proactive rather than reactive — minimizing risks, enhancing compliance and strengthening critical infrastructure security.
Felipe Sabino Costa, Sc, MBA, PMP, CCNA, CISA-US DHS, is the senior product marketing manager of networking and cybersecurity for Moxa Americas Inc. Edited by Sheri Kasprzak, managing editor, Automation & Controls, WTWH Media, [email protected].
