Bridging the Gap: Securing Operational Technology in an Evolving Cyber Landscape

By Riccardo Galbiati, Regional Chief Security Officer, JAPAC, at Palo Alto Networks

In today’s rapidly evolving technological landscape, the integration of new technologies into existing industrial systems presents a formidable challenge. This complexity arises primarily from the inherent differences between Operational Technology (OT) and Information Technology (IT). While IT systems are designed for rapid innovation and security updates, OT systems often consist of legacy infrastructures that were never intended to interface with modern IT frameworks. This article explores the challenges of securing OT environments, particularly in the resources industry, and outlines strategies for enhancing cybersecurity through collaboration, predictive AI, and a proactive security approach.

The Challenge of Legacy Systems

Updating legacy OT systems to meet contemporary IT security standards is no small feat. OT systems, which control critical physical processes and machinery, prioritize reliability and longevity, often operating for years or even decades without significant changes. In contrast, IT systems are characterized by their flexibility and adaptability, frequently undergoing updates to counter emerging security threats. This dichotomy creates a significant challenge for organizations striving to secure their operations against increasingly frequent cyber threats.

A recent study by Palo Alto Networks revealed that 82% of OT and IT business leaders in Australia reported experiencing a cyberattack in the past year, positioning them as the fourth largest target globally. As the convergence of IT and OT environments continues, the urgency to secure these systems has never been greater.

Embedding Security from the Start

One of the most effective lessons from the IT world that can be applied to OT is the principle of “secure by design.” Modern IT security practices have shifted from the outdated approach of “securing after you build” to “securing while you build.” This proactive stance is essential in dynamic environments where changes are frequent and can leave exploitable gaps if security measures are not integrated from the outset.

In the OT realm, where systems are more static, retrofitting security into established architectures can lead to friction and potential disruptions. Therefore, it is crucial to embed security controls—such as network segmentation, traffic anomaly detection, and virtual patching—during the design and deployment phases of OT systems. By consolidating these security functions into unified platforms, organizations can simplify management and reduce the complexity associated with coordinating multiple point products.

Fostering Collaboration Between IT and OT Teams

As the lines between IT and OT continue to blur, fostering collaboration between these two domains becomes imperative. Organizations must bridge the knowledge gap between the operational needs of industrial systems and the dynamic landscape of IT security. IT professionals bring expertise in cybersecurity best practices, while engineers possess in-depth knowledge of operational contexts and system functionalities.

However, a significant disconnect persists. According to the Palo Alto Networks study, 40% of respondents described the relationship between OT and IT as frictional, with only 14% indicating alignment between their teams. To enhance resilience against cyber threats, organizations must cultivate a collaborative approach that integrates technological expertise with operational insights.

Leveraging Predictive AI to Bridge the Security Gap

The rise of artificial intelligence (AI) presents both challenges and opportunities for the resources industry. The same Palo Alto Networks report indicated that 75% of OT and IT leaders in Australia view AI-driven attacks on OT as a significant threat. Conversely, 80% recognize the potential of AI for defensive purposes.

Predictive AI is a groundbreaking advancement that can help identify and prevent potential cyber threats or operational disruptions before they occur. By analyzing patterns of behavior at the network and endpoint levels, predictive AI can match the tactics, techniques, and procedures (TTPs) employed by malicious actors, enabling organizations to anticipate and mitigate threats in real time.

Additionally, AIOps (AI Operations) has evolved to include predictive capabilities related to operational disruptions. AI models can analyze vast datasets containing performance and device telemetry to identify when network and security assets are nearing capacity or experiencing malfunctions. The next evolution of predictive AI in cybersecurity and operational technology will likely involve automation, where AI models will not only identify threats but also execute remediation actions autonomously.

The Roadmap to an Effective Security Strategy

As cyber threats become increasingly sophisticated, the risks to industrial operations grow exponentially. Modernizing OT systems is a crucial step in securing critical infrastructure. However, this endeavor is not merely a technical challenge; it is a journey that requires a comprehensive approach.

By embracing proven security strategies from the IT space, fostering collaboration between IT and OT professionals, and implementing AI-powered tools, organizations can pave the way for a safer industrial landscape. This proactive approach will not only enhance resilience against cyber threats but also future-proof the critical infrastructure of tomorrow.

In conclusion, the integration of IT and OT security is not just a necessity; it is an opportunity to create a more robust and secure operational environment. By learning from the past and leveraging innovative technologies, organizations can navigate the complexities of the digital landscape and emerge stronger in the face of evolving cyber threats.