Siamese neural network for intelligent information security control in multi-robot systems

Abstract

Anomaly detection of the robot system behavior is one of the important components of the information security control. In order to control robots equipped with many sensors it is difficult to apply the well-known Mahalanobis distance which allows us to analyze the current state of the sensors. Therefore, the Siamese neural network is proposed to intellectually support the security control. The Siamese network simplifies the anomaly detection of the robot system and realizes a non-linear analogue of the Mahalanobis distance. This peculiarity allows us to take into account complex data structures received from the robot sensors.