Cybersecurity Integration in Systems Engineering

🚀 𝐍𝐞𝐰 𝐏𝐮𝐛𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧! 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐭𝐡𝐞 𝐂𝐑𝐀 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐈𝐨𝐓 𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞: 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬, 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬, 𝐚𝐧𝐝 𝐁𝐞𝐬𝐭 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐞𝐬 Proud to share our newest peer-reviewed article in Information (MDPI), co-authored with Miguel Ángel Ortega Velázquez, Iris Cuevas Martinez, and Dr. Antonio J. Jara (myself as ISACA CISM/CISA/AAIA). 𝘛𝘩𝘪𝘴 𝘸𝘰𝘳𝘬 𝘢𝘳𝘳𝘪𝘷𝘦𝘴 𝘢𝘵 𝘢 𝘤𝘳𝘶𝘤𝘪𝘢𝘭 𝘮𝘰𝘮𝘦𝘯𝘵, 𝘢𝘴 𝘵𝘩𝘦 𝘌𝘜 𝘊𝘺𝘣𝘦𝘳 𝘙𝘦𝘴𝘪𝘭𝘪𝘦𝘯𝘤𝘦 𝘈𝘤𝘵 (𝘊𝘙𝘈) 𝘣𝘦𝘤𝘰𝘮𝘦𝘴 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘪𝘮𝘱𝘢𝘤𝘵𝘧𝘶𝘭 𝘳𝘦𝘨𝘶𝘭𝘢𝘵𝘪𝘰𝘯 𝘧𝘰𝘳 𝘐𝘰𝘛 𝘮𝘢𝘯𝘶𝘧𝘢𝘤𝘵𝘶𝘳𝘦𝘳𝘴 𝘪𝘯 𝘵𝘩𝘦 𝘤𝘰𝘮𝘪𝘯𝘨 𝘺𝘦𝘢𝘳𝘴. 🔥 𝐓𝐨𝐩 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 1️⃣ 𝐀 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 𝐦𝐞𝐭𝐡𝐨𝐝𝐨𝐥𝐨𝐠𝐲 𝐭𝐨 𝐜𝐨𝐧𝐯𝐞𝐫𝐭 𝐥𝐞𝐠𝐚𝐥 𝐂𝐑𝐀 𝐭𝐞𝐱𝐭 𝐢𝐧𝐭𝐨 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐫𝐞𝐚𝐥𝐢𝐭𝐲: We introduce a two-phase framework: • Phase 1: Systematically transform CRA Articles 13–14 and Annexes into atomic, testable engineering requirements. • Phase 2: Apply Analytic Hierarchy Process (AHP) quantitative scoring to produce a defensible readiness metric. 2️⃣ 𝐀 𝐟𝐮𝐥𝐥 𝐥𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞-𝐛𝐚𝐬𝐞𝐝 𝐂𝐑𝐀 𝐜𝐡𝐞𝐜𝐤𝐥𝐢𝐬𝐭 𝐟𝐨𝐫 𝐈𝐨𝐓 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐬: From secure design to post-market obligations, the paper provides an actionable DevSecOps-aligned checklist. 3️⃣ 𝐀 𝐝𝐞𝐟𝐞𝐧𝐬𝐢𝐛𝐥𝐞 𝐫𝐢𝐬𝐤-𝐛𝐚𝐬𝐞𝐝 𝐰𝐞𝐢𝐠𝐡𝐭𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥 𝐮𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜 𝐇𝐢𝐞𝐫𝐚𝐫𝐜𝐡𝐲 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 (𝐀𝐇𝐏): We derive consistent domain weights, ensuring mathematically validated prioritization of CRA domains. 4️⃣ 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐯𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 through the TRUEDATA project funded by INCIBE - Instituto Nacional de Ciberseguridad: We applied the full model to a large industrial OT cybersecurity project (water infrastructure) with Neoradix Solutions AirTrace Bersey UCAM Universidad Católica San Antonio de Murcia at the pilots with the support of the Confederación Hidrográfica del Segura, O.A., Mancomunidad De Los Canales De Taibilla, and FRANCISCO ARAGÓN. 5️⃣ 𝐂𝐥𝐞𝐚𝐫 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐠𝐮𝐢𝐝𝐚𝐧𝐜𝐞. The paper provides best practices for SBOM automation, PSIRT & CVD setup, Secure-by-design, OTA, monitoring, attestation, documentation and conformity assessment Our aim from Libelium with this paper is to give the industry a practical, structured, and evidence-based way to operationalize compliance and strengthen cybersecurity by design. 𝐓𝐑𝐔𝐄𝐃𝐀𝐓𝐀 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐞𝐬 𝐡𝐨𝐰 𝐭𝐡𝐞 𝐦𝐞𝐭𝐡𝐨𝐝𝐨𝐥𝐨𝐠𝐲 𝐚𝐩𝐩𝐥𝐢𝐞𝐬 𝐭𝐨 𝐡𝐢𝐠𝐡-𝐬𝐭𝐚𝐤𝐞𝐬 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐬𝐲𝐬𝐭𝐞𝐦𝐬. 𝐓𝐡𝐞 𝐂𝐑𝐀 𝐢𝐬 𝐧𝐨𝐭 “𝐣𝐮𝐬𝐭 𝐚𝐧𝐨𝐭𝐡𝐞𝐫 𝐫𝐞𝐠𝐮𝐥𝐚𝐭𝐢𝐨𝐧”, 𝐢𝐭 𝐢𝐬 𝐭𝐡𝐞 𝐧𝐞𝐰 𝐛𝐚𝐬𝐞𝐥𝐢𝐧𝐞 𝐟𝐨𝐫 𝐈𝐨𝐓 𝐭𝐫𝐮𝐬𝐭 𝐢𝐧 𝐄𝐮𝐫𝐨𝐩𝐞. 👉 Download here: https://lnkd.in/dQu54qE2 European Union Agency for Cybersecurity (ENISA) Felix A. Barrio (PhD, CISM) Global Cybersecurity Forum SITE سايت Betania Allo Axon Partners Group ISACA ISACA VALENCIA

The Cybersecurity and Infrastructure Security Agency (CISA), together with other organizations, published "Principles for the Secure Integration of Artificial Intelligence in Operational Technology (OT)," providing a comprehensive framework for critical infrastructure operators evaluating or deploying AI within industrial environments. This guidance outlines four key principles to leverage the benefits of AI in OT systems while reducing risk: 1. Understand the unique risks and potential impacts of AI integration into OT environments, the importance of educating personnel on these risks, and the secure AI development lifecycle.  2. Assess the specific business case for AI use in OT environments and manage OT data security risks, the role of vendors, and the immediate and long-term challenges of AI integration 3. Implement robust governance mechanisms, integrate AI into existing security frameworks, continuously test and evaluate AI models, and consider regulatory compliance.  4. Implement oversight mechanisms to ensure the safe operation and cybersecurity of AI-enabled OT systems, maintain transparency, and integrate AI into incident response plans. The guidance recommends addressing AI-related risks in OT environments by: • Conducting a rigorous pre-deployment assessment. • Applying AI-aware threat modeling that includes adversarial attacks, model manipulation, data poisoning, and exploitation of AI-enabled features. • Strengthening data governance by protecting training and operational data, controlling access, validating data quality, and preventing exposure of sensitive engineering information. • Testing AI systems in non-production environments using hardware-in-the-loop setups, realistic scenarios, and safety-critical edge cases before deployment. • Implementing continuous monitoring of AI performance, outputs, anomalies, and model drift, with the ability to trace decisions and audit system behavior. • Maintaining human oversight through defined operator roles, escalation paths, and controls to verify AI outputs and override automated actions when needed. • Establishing safe-failure and fallback mechanisms that allow systems to revert to manual control or conventional automation during errors, abnormal behavior, or cyber incidents. • Integrating AI into existing cybersecurity and functional safety processes, ensuring alignment with risk assessments, change management, and incident response procedures. • Requiring vendor transparency on embedded AI components, data usage, model behavior, update cycles, cybersecurity protections, and conditions for disabling AI capabilities. • Implementing lifecycle management practices such as periodic risk reviews, model re-evaluation, patching, retraining, and re-testing as systems evolve or operating environments change.

🔐 𝗦𝗲𝗰𝘂𝗿𝗶𝗻𝗴 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝗦𝘆𝘀𝘁𝗲𝗺𝘀: 𝗔 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗜𝗺𝗽𝗲𝗿𝗮𝘁𝗶𝘃𝗲 🌐⚙️ As industrial operations increasingly rely on distributed control architectures—with SCADA servers, HMI stations, remote PLCs, satellite links, and RF/WAN connectivity—the cyber threat landscape becomes more complex and dangerous. Here’s a snapshot from a typical Industrial Distributed Control System (IDCS) involving centralized control centers and geographically dispersed remote stations. While this setup enables efficiency and real-time visibility, it also exposes critical assets to significant cyber risks if not properly secured. 🚨 🔍 So, how do we secure such an architecture end-to-end? Here are key cybersecurity measures every industrial organization should implement: 🔐 𝟭. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 (𝗜𝗧/𝗢𝗧 𝗕𝗼𝘂𝗻𝗱𝗮𝗿𝘆 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝗶𝗼𝗻) • Strictly separate the Control Center LAN (IT) from the Process Control Network (OT) using firewalls and industrial demilitarized zones (iDMZ). • Implement unidirectional gateways where data flow must be one-way (e.g., from PLCs to SCADA). 🛡️ 2. Secure Remote Communications • Use VPNs with strong encryption for all WAN and satellite/RF communications. • Replace legacy modems with hardened industrial communication devices that support authentication and encryption. 🔍 3. PLC and Device Hardening • Disable unused ports and services on PLCs. • Apply secure boot, firmware validation, and role-based access control (RBAC) at the edge. 📊 4. Monitoring and Detection • Integrate an Industrial SIEM and deploy passive network monitoring tools (e.g., Deep Packet Inspection for SCADA protocols). • Deploy anomaly detection systems near PLCs and RTUs to identify abnormal process behavior. 🧩 5. Identity and Access Management (IAM) • Implement multi-factor authentication (MFA) for engineering and HMI stations. • Enforce least privilege access and maintain an audit trail of operator actions. 📆 6. Patch Management and Asset Inventory • Maintain a real-time asset inventory of all SCADA components and remote devices. • Regularly validate firmware versions and plan patch cycles aligned with operational downtimes. 🧰 7. Incident Response and Resilience • Design and rehearse cyber-physical incident response plans specific to industrial contexts. • Deploy redundant paths and fallback systems (e.g., local PLC logic if communication is lost). ⚠️ Final Thought: As industries digitalize, attackers are shifting their focus from IT to OT environments. Securing these Distributed Control Environments is not just a technical requirement—it’s a business continuity imperative. 🏭🛡️ 🔗 Let’s prioritize Zero Trust principles, cyber resilience, and secure-by-design architectures for industrial systems. #CyberSecurity #OTSecurity #SCADA #IndustrialCybersecurity #ZeroTrust #IIoT #SCADAsecurity #DCS #Resilience #CriticalInfrastructure #ICS #CybrForge

𝗦𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗮𝗻 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 𝗳𝗿𝗼𝗺 𝗦𝗰𝗿𝗮𝘁𝗰𝗵? 𝗛𝗲𝗿𝗲’𝘀 𝗠𝘆 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 Industrial operations run our daily lives—think metro trains, water systems, power grids, even the checkout at your supermarket. All of this is powered by Operational Technology (OT), which directly impacts physical processes and public safety. But OT systems are under attack more than ever. Many still run on 20-year-old software, are tough to update, and can’t just be “patched” like regular IT systems. Real-world consequences can be huge: from power outages to critical failures in hospitals and transport. So, where do you even begin with OT security? Here’s my take (as discussed with Prabh in his latest podcast): 1. Understand What You Have: Start with an asset inventory. Visibility is everything. You can’t protect what you don’t know exists. 2. Identify Risks: Figure out what could go wrong. Every asset, old or new, has its own risks—especially those running legacy software. 3. Involve Your Operations Team: OT staff are focused on keeping the plant running. Bring them into the conversation from Day 1. Awareness and buy-in are key. 4. Tailor Your Approach: There’s no copy-paste. Every factory, plant, or substation is unique. Build processes that fit your environment, not just what the textbook says. 5. Prioritize the Basics: ✏️ Incident response plans: Who does what when things go wrong? ✏️ Control remote access: Limit those USB sticks, dongles, and remote sessions. ✏️ Access control: Don’t give everyone full admin rights. ✏️ Network segmentation: Create “islands” to limit the spread if something goes wrong. ✏️ Training: Make cybersecurity real for your OT staff. One weak link can break everything. 6. Use the Right Frameworks: IEC 62443 is a great start, covering people, process, and technology. Pair it with industry guidance like NIST 800-82. 7. Continuous Improvement: Cybersecurity isn’t a one-off project. Monitor, learn, and adapt. OT threats evolve—your defenses should too. Why does all this matter? Because OT is critical. Downtime isn’t just about lost money—it can risk lives. And with more cyber threats targeting OT, our collective vigilance matters now more than ever. I’ve built the OT Security Huddle community for this reason: to share, discuss, and solve real OT security problems together. Whether you’re just getting started or deep into your journey, you’re not alone. Watch my full conversation with Prabh Nair for all the details—link below! https://lnkd.in/gjYCnt7j #OTSecurity #Cybersecurity #IEC62443 #CriticalInfrastructure #IndustrialSecurity

Here I attached the Cybersecurity Technology Stack. This poster is a complete visual guide to the key cybersecurity tools and technologies across all major categories from SIEM, EDR, XDR, SOAR, TIP, PAM, CSPM to deception technologies, UEBA and more. I created this to help professionals and newcomers get a clearer picture of what solutions are available and how they fit into the larger cybersecurity ecosystem. When I first started working in cybersecurity operations, most environments focused heavily on perimeter defence and endpoint protection. But attackers have evolved. Today, a proper setup requires multiple integrated layers that work together. No single tool is enough. What matters is how these tools connect to give visibility, control and speed in detection and response. If you're building or reviewing your cybersecurity stack, these are the key areas I recommend you consider: 1. Visibility with SIEM •Start with a strong SIEM platform. This will collect logs across your infrastructure from endpoints, firewalls, cloud and identity systems and help detect patterns or anomalies. 2. Real-time Threat Detection with EDR or XDR •Next, deploy EDR to get deep visibility into endpoint activities. If your budget allows, move towards XDR to combine endpoint, network and cloud telemetry into one detection layer. 3. Response Automation with SOAR •As alerts come in, you need a fast and consistent way to respond. A SOAR platform can automate triage, enrich alerts with threat intel and reduce the time analysts spend on manual tasks. 4. Threat Intelligence Integration •No matter how good your SIEM or EDR is, you need context. Use Threat Intelligence Platforms (TIP) to enrich data with external threat indicators and insights. 5. Secure Privileged Access with PAM •If an attacker gets access to a privileged account, the damage can be severe. Implement PAM to secure, manage and audit access to critical systems and credentials. 6. Vulnerability Management •A well-monitored environment still becomes weak if patching is not managed. Use vulnerability scanners and patch management systems to identify and remediate weaknesses quickly. 7. Cloud Security Posture and Identity Management •As more workloads move to the cloud, ensure you have CSPM tools and proper IAM controls in place to prevent misconfigurations and abuse of identity-based access. 8. Advanced Detection with NDR, UEBA, and Deception •For mature setups, consider adding Network Detection & Response, User Behaviour Analytics and deception technologies. These give you deeper layers of defence and help detect stealthy attacks. Building a modern cybersecurity setup is not about chasing tools, but designing an architecture where each solution complements the other. You want detection, correlation, automation and response to happen as smoothly as possible. This is the mindset behind the stack I designed. Every component in this poster plays a role in defending against modern threats.

Modern Security Architecture: A Layered Approach to Modern Security Architecture In today’s hyperconnected world, cybersecurity is no longer a siloed IT concern—it’s a strategic imperative. As digital transformation accelerates, organizations must adopt a holistic, layered security architecture that not only defends but anticipates, adapts, and evolves. The “Modern Security Architecture” framework offers a powerful blueprint for building resilient digital ecosystems. Let’s break it down: Layered Defense: From API to Infrastructure Each layer in this architecture addresses a specific domain of risk, creating a multi-dimensional shield: Layer 7: Application Layer API Security & Gateways: Protects data exchange between services. Web Application Firewalls (WAF): Defends against common web exploits. Layer 6: Data Governance Privacy by Design: Embeds compliance into system architecture. Data Loss Prevention (DLP): Prevents unauthorized data exfiltration. Layer 5: Data Protection Encryption & Secure Serialization: Ensures data integrity and confidentiality. Layer 4: Identity & Access Zero Trust Access (ZTA): Trust no one, verify everything. Adaptive MFA & Just-In-Time Access: Dynamic authentication based on context. Layer 3: Network Security SASE & D-WAN: Secure access service edge for cloud-first environments. Layer 2: Transport Security Secure Protocols & Session Resilience: Fortifies data in transit. Layer 1: Physical & Operational Security VLAN Segmentation, MACsec, NAC: Controls access at the data link level. OT/ICS Security: Protects critical infrastructure systems. Prevention First: Build Secure by Design Security must shift left—integrated early in the development lifecycle: Threat Modeling: Identify vulnerabilities before they manifest. DevSecOps: Embed security into CI/CD pipelines. Secure by Design: Architect systems with security as a foundational principle. Monitoring & Response: Stay Vigilant Detection and response capabilities are the backbone of resilience: XDR / SOAR: Unified threat detection and automated response. Threat Intelligence: Real-time insights into emerging threats. Continuity & Resilience: Ensure business operations withstand disruptions. Final Thoughts: Security is no longer just about firewalls and antivirus—it’s about architecture, culture, and continuous adaptation. Whether you're a CTO, CISO, or enterprise strategist, embracing this layered model can help future-proof your organization against evolving threats. Let’s build secure, resilient systems—layer by layer. #CyberSecurity #ZeroTrust #DevSecOps #SecurityArchitecture #DigitalTransformation #EnterpriseSecurity #TechLeadership

The new era of cyber threats in the Middle East isn’t about data - it’s about control over vital resources. For years, I’ve tracked cyberattacks on critical infrastructure. But today’s events in the Middle East signal a dramatic shift - not just a security issue, but a challenge to economic stability, energy control, and national resilience. Key Trends Impacting Middle Eastern CNI: 73.2% of cyberattacks now target Operational Technology (OT) systems. A 300% surge in DDoS attacks is disrupting energy, oil & gas, and government networks. State-backed groups are increasingly infiltrating ICS and SCADA environments. A Timeline of Escalation: - 2023: A major supply chain breach attempt shakes the region. - 2024: Cyber intrusions into power grids rise sharply. - February 2024: An OT-targeted attack forces an industrial facility to shut down temporarily. These aren’t isolated incidents - they form part of a coordinated geopolitical strategy aimed at undermining essential services. Bridging the IT-OT Security Gap: Historically, IT and OT systems operated in separate silos. However, as digitalization merges these environments, vulnerabilities emerge: - Outdated OT Systems: Many run on legacy software, not designed for today’s cybersecurity challenges. - Interconnected Breaches: An IT breach can now lead to access in OT environments. - Lack of Real-Time Monitoring: Without continuous oversight, industrial networks remain exposed. The consequences are real: compromised oil transportation, manipulated water treatment systems, and governments scrambling to rewrite security policies overnight. The Path Forward: A Resilience-First Strategy To protect our critical infrastructure, we must evolve beyond compliance: - Integrated IT-OT Security: Achieve full visibility across both environments. - AI-Powered Threat Detection: Use real-time, AI-driven anomaly detection. - Zero Trust Architectures: Continuously verify every device and user. - Supply Chain Vigilance: With 82% of incidents linked to vendor vulnerabilities, monitoring is crucial. - Adaptive Cybersecurity: Embrace red teaming and robust incident response planning. Let’s Connect: How is your organization addressing the IT-OT security gap? I’d love to hear your insights and explore strategies to build resilient critical infrastructure together. Feel free to reach out or schedule a quick chat with my team. Meeting link in the comment section. My team and I are working on something critical and valuable. We’re in stealth mode, developing a platform to strengthen CNI security against evolving OT threats. By April, we’ll begin building a prototype to address these critical challenges head-on. #CNI #CyberSecurity #MiddleEast #OTSecurity #ThreatDetection #ZeroTrust #CriticalInfrastructure

Creating a next-generation OT SOC is less about chasing the latest tools and more about reshaping security teams so that IT and #OTsystems are no longer islands. As OT systems increasingly connect to the corporate IT environment and other IIoT systems, cyber defenders will need integrated visibility and a shared data set to recognize patterns and complexities in threat intelligence and correlation. To do this, top #industrial companies are shifting away from integrated teams and toward a single cyber team with integrated skills and abilities through convergence, delivering real value when it enables real-time analysis and automation, rather than noise and unnecessary information. Industrial Cyber spoke with industry experts to understand how the convergence of IT, #OT, and increasingly interconnected systems is reconfiguring #cybersecurity team structures, decision-making, and day-to-day operations across #criticalinfrastructure. They also explore where convergence has moved beyond theory to deliver tangible improvements in OT security, operational reliability, and system resilience. “IT risks are now OT risks and vice versa. Leveraging operational data inevitably demands the convergence of IT and OT, meaning corporate IT threats (malware, etc.) can directly affect OT systems,” Mark Ryan, team lead of DNV Cyber, said. “The line between what is OT and what is IT is blurred. Each customer, scenario, and request proposal shows a unique fingerprint of architectural, process, and industry-related concerns. Our OT SOC development program integrated industrial network sensors with enterprise SOC, enabling holistic monitoring of plants and offices together.” Saltanat Mashirova, senior manager for OT cybersecurity at CPX, sees IT/OT convergence fundamentally reshaping cybersecurity teams from siloed IT and OT functions into a more collaborative, risk-driven operating model. “In day-to-day operations, this means shared visibility, shared workflows, and much tighter collaboration between IT, OT engineers, and operations." “It’s more important than ever that teams are cross-functional, made up of ‘T-shaped’ members who are deeply skilled in their area of expertise, but also broad enough to understand and communicate with the ‘other side,’” David Formby, co-founder and CEO/CTO of Fortiphyd Logic, said. “Teams where IT has cross-trained on OT and OT cross-trained on IT are able to make more intelligent, consequence-driven decisions on triage and escalation of events.” Zakhar Bernhardt, an OT/ICS cybersecurity consultant at German automation company anapur AG, said that #OTenvironments are becoming more connected to IT systems and day-to-day business operations. “As a result, IT teams are increasingly involved in OT security and processes. For many organizations, OT directly supports core revenue, so protecting these environments is no longer optional.” 

In a recent discussion, the topic of event response in process environments came up. The group was a mix of IT, OT, and engineering roles and backgrounds. There was good input, with some 'IT-centric' perspectives, based on existing IRPs in place, focused on network security, isolation, segmentation, logging, SIEM, SOAR, EDR/MDR, SOC, IDS, IPS, etc. We widened the aperture, looking beyond Ethernet-connected devices like PLCs, HMIs, and Windows-based workstations and servers, addressing vulnerabilities and failures within the physical layer—field devices, instrumentation, and serial and industrial protocols (Modbus RTU, RS-485, HART/WirelessHART, PROFIBUS, and PROFINET, etc.) integral to safe and reliable process control. The significance of these layers can be common shortcomings in existing IRPs where security, IT, OT teams, asset & process owners, must converge in development of adequate response planning. Field devices (transmitters, actuators, sensors, and valves) and serial protocols represent the primary interface between digital control systems and the physical process. A failure or compromise at this level may not be detectable by conventional IT cybersecurity monitoring tools, more importantly can have cascading impact that takes place rapidly, degrading safety and reliability proportionately. Field-level anomalies frequently trigger, as mentioned previously, cascading impacts across multiple system layers. For instance, a malfunctioning RTD sensor feeding incorrect temperature values into a PLC could propagate through PID loops, triggering alarms or auto-shutdowns across unrelated systems. IRPs should consider PHA, SIS, process flows/lockouts, fail-safe, restoration sequencing/timing of process state. Resilience requires acknowledging the physical realities of field-level instrumentation, integrating vendor or component-specific tools and diagnostics, and aligning incident response with the deterministic and safety-critical nature of industrial processes. By addressing these gaps, engineering personnel, asset and process owners, in partnership with IT and security recovery teams ensure faster recovery, safety, productivity, and reliability, in the face of both cyber and physical disruptions.

🔐 AI Governance Is No Longer Optional — It Must Be Integrated Into Cybersecurity Training & GRC Now As AI systems become embedded across enterprise security, threat detection, identity workflows, and automation pipelines, the risk surface is expanding faster than traditional controls can keep up. Effective AI governance must now be treated as a first-class component of cybersecurity programs—embedded directly into training, operational security, and GRC frameworks. Here’s how forward-leaning security teams are doing it: 🔎 1. Establish an AI Governance Framework Use structured governance models that mirror established security frameworks: AI risk classification: Identify AI systems, data flows, decision impact, and safety-critical components. Model lifecycle controls: Apply versioning, approval gates, drift monitoring, and performance validation. Security & privacy baselines: Enforce threat modeling, data minimization, PII controls, and red-team evaluations against prompt injection and model exploitation. 🛡 2. Integrate AI Threat Modeling Into Training Extend existing secure engineering and AppSec training to include: AI/ML-specific threat scenarios: Model poisoning, adversarial inputs, jailbreaks, training-data leakage. Secure prompt engineering: Guardrails, context restriction, least-privilege prompts, and API-level access management. Model behavior validation: Teach staff how to evaluate hallucination risk, output integrity, and system response boundaries. Supply chain considerations: Validate datasets, model sources, vendor controls, and licensing compliance. 📘 3. Embed AI Governance Into GRC Processes Treat AI systems like any other technology subject to governance, but with enhanced oversight: Policy Mapping: Align AI use with ISO 42001, NIST AI RMF, and existing enterprise security policies. AI Risk Register Entries: Document model usage, data categories, risk ratings, and compensating controls. Continuous Monitoring: Measure model drift, decision error rates, anomalous outputs, and access patterns. Control Families: Integrate AI-specific controls into your existing GRC stack—access control, data classification, audit logging, third-party risk, and model deployment workflows. 🧩 4. Build AI Governance Into Incident Response AI incidents require new playbooks: Model-driven incident categories: Output manipulation, model degradation, training data exposure, unauthorized fine-tuning. Forensic Support: Log prompts, context injection attempts, and model inference metadata. Rollback Mechanisms: Maintain approved model versions, data lineage tracking, and automated reversion paths. #Cybersecurity #AIGovernance #GRC #CyberRiskManagement #AIsecurity #InformationSecurity #SecurityEngineering #NISTAI #ISO42001 #ThreatModeling #CyberTraining #CISO #RiskAndCompliance #AIMaturity