AI And ML Are Needed To Strengthen The Cybersecurity Posture Of Critical Infrastructure – Go Health Pro

Critical Infrastructure (CI) cybersecurity has witnessed increasing breaches. Geopolitical tensions have contributed to the trend, along with the fact that state-linked actors have more resources at their disposal to breach industrial organisations.

Attacks on critical infrastructure spurring OT and IoT cybersecurity spending for industrial OT sectors which ABI Research forecasts to reach almost US$4.6 billion by 2027.

Michael Amiri

“Industrial cybersecurity is witnessing an expansion of updated technology offerings, including advanced firewalls tailored for harsh environments, segmentation technologies that provide one-way data flows, and advanced monitoring and visibility solutions,” says Michael Amiri, senior Industrial and IoT Cybersecurity analyst at ABI Research.

Industrial cybersecurity vendors are also upping their game and providing customers with innovative solutions. Vendors such as Claroty, Otorio, Palo Alto Networks, and Dragos offer real-time monitoring and visibility into the industrial network by deploying machine learning (ML) and artificial intelligence (AI) to monitor network traffic behaviour.

Amiri says real-time data analysis allows the collection of real-time data from the factory floor or remote operations, which were difficult to access before digitalization. This in turn improves decision-making and operational strategies.

Industrial cybersecurity vendors are increasingly deploying advanced technologies such as ML. AI and ML are not buzzwords, but crucial to achieve a comprehensive OT/ICS cyber strategy. AI and ML algorithms exhibit superior capabilities in detecting anomalies and real threats in network traffic.

“They provide better solutions than traditional rule-based approaches toward network security,” Amiri concludes.

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