IXDen, a failure prediction and cybersecurity specialist, has created an autonomous software that combines OT failure predictions and cybersecurity in a user-friendly, all-in-one solution. The IXDen solution analyses data from sensors and industrial equipment to spot anomalies in data transactions that signal a cyberattack or OT failure. The fully autonomous Machine Learning (ML) and AI software creates a dynamic behavioural model of each device, both in isolation and as part of interrelated process dependencies.
Centralized approach to monitor the whole OT system at a glance
The software monitors 100 per cent of data transactions at the sensor level, spotting changes in behaviour that signal a cyberattack or equipment failure. The data is then used to summarise the OT health in a single numerical score, highlighted by a traffic light performance indicator, so operations managers can monitor the whole OT system at a glance, with the ability to drill down on the root causes of problems.
IXDen’s approach to IoT device security and authentication enables detecting security threats and abnormal behavior on all levels, from sensor and device to gateway, PLC and RTU. To detect even the slightest anomaly in the sensor data while protecting against tampering, IXDen implements unparallel Machine Learning and AI algorithms combined with proprietary mathematics, advanced behavioral and statistical modeling and analysis.