About Kaspersky Machine Learning for Anomaly Detection
The early anomaly detection system known as Kaspersky Machine Learning for Anomaly Detection (hereinafter also referred to as Kaspersky MLAD or "the application") is specialized software designed to prevent failures, accidents or degradation of industrial installations, technological processes, and complex cyberphysical systems. By analyzing telemetry data using machine learning techniques (artificial intelligence), Kaspersky MLAD detects signs of an abnormal situation before it is detected by traditional monitoring systems.
Kaspersky MLAD detects anomalies in industrial processes regardless of their causes. Anomalies may be caused by the following:
Physical factors, such as damage to equipment or malfunctioning sensors.
Human factors (such as intentional or inadvertent inappropriate actions of the operator, hardware configuration, change of operating modes or equipment, or switch to manual control).
Allows you to receive telemetry data over HTTP, OPC UA, MQTT, AMQP, CEF, and WebSocket protocols, and via a specialized protocol over HTTPS from Kaspersky Industrial CyberSecurity for Networks.
Displays historical and real-time data as graphs according to the specified sets of tags.
Detects and handles terminations and interruptions of the incoming data stream, and restores missed observations.
Sends alerts about the detection of certain events, patterns, or values of the event parameters received by the Event Processor in the data stream from the monitored asset.