Kaspersky Machine Learning for Anomaly Detection

Kaspersky MLAD architecture

December 6, 2023

ID 247981

Kaspersky MLAD is installed on a server that meets the hardware and software requirements. The Kaspersky MLAD Server centrally stores information about application services and connectors and provides a single web user interface for managing them.

Access to individual services or application connectors is not provided.

When installing Kaspersky MLAD, all application connectors and services are hosted on the same server and interact with each other through an internal virtual network that is isolated from external systems.

Kaspersky MLAD includes specially prepared ML models, and the following services and connectors:

ML model

An ML model is a model created for a specific facility based on machine learning algorithms and/or diagnostic rules using telemetry data from this facility. The ML model detects incidents.

An ML model can be provided as part of the Kaspersky MLAD Model-building and Deployment Service or created using the model builder.

Kaspersky MLAD services

Kaspersky MLAD services comprise a set of core application services supplied to each monitored asset. Kaspersky MLAD includes the following services:

  • Anomaly Detector. Uses an ML model to process data and detect anomalies.
  • Event Processor. Uses machine learning methods based on a semantic neural network to identify patterns and anomalous sequences of events.
  • Stream Processor. Brings telemetry data received from the monitored asset at arbitrary real-time moments to a uniform temporal grid.
  • Trainer. Performs repeated or additional training of an existing ML model based on the new telemetry data obtained by Kaspersky MLAD for a specific monitored asset.
  • Similar Anomaly. Identifies and groups together similar incidents.
  • Message Broker. Exchanges data between Kaspersky MLAD services.
  • Time Series Database. Stores time series of observed tag values, tag values predicted by the ML model, and prediction errors.
  • Keeper. Performs routing of the telemetry data that should be saved in the database.
  • Database. Stores all configuration settings of Kaspersky MLAD.
  • API Server. Supports operation of the internal interfaces of Kaspersky MLAD.
  • Web Server. Supports operation of the Kaspersky MLAD web interface.
  • Logger. Stores Kaspersky MLAD operation logs.
  • Mail Notifier. Sends emails with incident registration notifications.

Connectors

Connectors are services that facilitate the exchange of data with external systems. For each protection object, you must select one of the following connectors:

  • KICS Connector. Supports interaction with Kaspersky Industrial CyberSecurity for Networks version 4.0 and later.
  • OPC UA Connector. Receives tags from industrial process control systems (ICS) according to the protocol described in the OPC Unified Architecture specification.
  • CEF Connector. Receives events from external sources (Industrial Internet of Things, network devices and applications) and returns messages in CEF (Common Event Format) registered by event analysis monitors.
  • MQTT Connector. Receives tags from ICS and sends messages about incidents via the MQTT (Message Queuing Telemetry Transport) protocol.
  • AMQP Connector. Receives tags from ICS and sends messages about incidents via AMQP (Advanced Message Queuing Protocol).
  • WebSocket Connector. Receives tags from ICS and sends messages about incidents via the WebSocket protocol.
  • HTTP Connector. Receives telemetry data from ICS in CSV files via HTTP POST requests.

The figure below shows a diagram of interaction between Kaspersky MLAD services.

The diagram describes Kaspersky MLAD interaction with external systems and Kaspersky MLAD components' interaction with each other.

Diagram of interaction between Kaspersky MLAD services

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