Leveraging proprietary AI and statistical, behavioral and Machine Learning analyses, IXDen’s patented technology enables to generate a unique device identity at any given moment based on historical knowledge of the sensors’ information, interdependencies, and correlations between hundreds of different physical measurements and parameters. IXDen detects any discrepancies in the system’s real vs. predicted behavior.
By simply installing a software agent on the IoT device, controller or any IoT hub, IT and OT teams can gain deeper insights of each device on a sensor, software, hardware and network level. Each unique, constantly changing device identity comprises hundreds of dynamic and static parameters related to both Security an Operations.
IXDen protects all edge devices, such as Industrial Controllers and sensors, by accessing raw sensor data – in addition to internal device hardware, software and network information
The ability to generate dynamic device identities enables to perform multi-factor authentication on IoT devices for the very first time. This assures authentic, untampered data in a safer and more secure IT/OT network environment.
Traditional anomaly detection solutions are based on passive data collection and utilizing statistical models, which require a learning period. They are lack of the ability to authenticate the device as a part of communication transaction. IXDen relies on deep analysis and understanding of the behavioral, physical nature of the collected data using AI and sophisticated behavioral models, which eliminates the need for prior learning. Parameter inter-dependencies analysis is used to significantly improve the quality of the authentication process, which further reduces the false positive and negative rate.
