Siemens Energy has launched the first AI-driven cybersecurity monitoring solution to proactively detect and prevent cyberattacks targeting critical infrastructure for all operating environments before they execute. The technology platform, Eos.ii, leverages AI and machine learning methodologies to gather and model real-time energy asset intelligence. MDR is able to collect raw IT and operational technology data from across an industrial operating environment, and then contextualise it in real time. It provides a unified picture of anomalous behaviour for defenders with actionable insights to stop attacks
Siemens Energy’s MDR system goes beyond conventional monitoring by achieving a deeper understanding of how digital systems relate to the real world. With its unified OT and IT data stream, it uses AI and digital twin technology to compare billions of real-time data points against correctly functioning assets. This provides context for Siemens’ analysts to determine not only which events are abnormal, but which are consequential. Notably, Siemens is one of the leading energy companies in the world to face cyberattacks.
54% of those surveyed expected an attack on critical infrastructure in the next 12 months. Furthermore, 25% of respondents reported being impacted by mega-attacks with expertise developed by nation-state actors. The study also found that 71% of survey respondents said that sophisticated attacks are a top challenge and 64% thought that complex attacks were among the top challenges.