Kaspersky Machine Learning for Anomaly Detection
- About Kaspersky Machine Learning for Anomaly Detection
- What's new
- Basic concepts of Kaspersky MLAD
- Kaspersky MLAD architecture
- Common deployment scenarios
- Telemetry and event data flow diagram
- Ports used by Kaspersky MLAD
- Installing and removing the application
- Installing the application
- Updating the application
- Backing up the application
- Rolling back the application to the previous installed version
- Scenario for restoring Kaspersky MLAD from a backup
- Getting started
- Starting and stopping Kaspersky MLAD
- Updating Kaspersky MLAD certificates
- First startup of Kaspersky MLAD
- Removing the application
- Kaspersky MLAD web interface
- Connecting to Kaspersky MLAD and terminating a user session
- Changing a user account password
- Selecting the localization language for the Kaspersky MLAD web interface
- Licensing the application
- Processing and storing data in Kaspersky MLAD
- System administrator tasks
- Managing user accounts
- Manage roles
- Managing incident notifications
- Configuring Kaspersky MLAD
- Configuring the main settings of Kaspersky MLAD
- Configuring the security settings of Kaspersky MLAD
- Configuring the Anomaly Detector service
- Configuring the Keeper service
- Configuring the Mail Notifier service
- Configuring the Similar Anomaly service
- Configuring the Stream Processor service
- Configuring the HTTP Connector
- Configuring the MQTT Connector
- Configuring the AMQP Connector
- Configuring the OPC UA Connector
- Configuring the KICS Connector
- Configuring the CEF Connector
- Configuring the WebSocket Connector
- Configuring the Event Processor service
- Configuring the statuses and causes of incidents
- Configuring logging of Kaspersky MLAD services
- Configuring time intervals for displaying data
- Configuring how the Kaspersky MLAD main menu is displayed
- Export and import of Kaspersky MLAD settings
- Managing assets and tags
- Creating an asset in the asset tree
- Changing the parameters of an asset in the asset tree
- Create tag
- Adding a tag to an asset
- Editing a tag
- Moving assets and tags
- Deleting an asset or tag
- Checking the current structure of tags
- Uploading tag and asset configuration to the system
- Saving tag and asset configuration to a file
- Working with the main menu
- Scenario: working with Kaspersky MLAD
- Viewing summary data in the Dashboard section
- Viewing incoming data in the Monitoring section
- Viewing data in the History section
- Viewing data in the Time slice section
- Viewing data for a specific preset in the Time slice section
- Selecting a specific branch of the ML model in the Time slice section
- Selecting a date and time interval in the Time slice section
- Navigating through time in the Time slice section
- Configuring how graphs are displayed in the Time slice section
- Working with events and patterns
- Working with incidents and groups of incidents
- Scenario: analysis of incidents
- Viewing incidents
- Viewing the technical specifications of a registered incident
- Viewing incident groups
- Studying the behavior of the monitored asset at the moment when an incident was detected
- Adding a status, cause, expert opinion or note to an incident or incident group
- Exporting incidents to a file
- Managing ML models
- Scenario: working with ML models
- Working with markups
- Working with imported ML models
- Working with manually created ML models
- Cloning an ML model
- Working with ML model templates
- Changing the parameters of an ML model
- Training a neural network element of an ML model
- Viewing the training results of an ML model element
- Preparing an ML model for publication
- Publishing an ML model
- Starting and stopping ML model inference
- Viewing the data flow graph of an ML model
- Removing an ML model
- Managing presets
- Managing services
- Troubleshooting
- When connecting to Kaspersky MLAD, the browser displays a certificate warning
- The hard drive has run out of free space
- The operating system restarted unexpectedly
- Cannot connect to the Kaspersky MLAD web interface
- Graphs are not displayed in the History and Monitoring sections
- Events are not transmitted between Kaspersky MLAD and external systems
- Cannot load data to view in the Event Processor section
- Data is incorrectly processed in the Event Processor section
- Events are not displayed in the Event Processor section
- Previously created monitors and the specified attention settings are not displayed in the Event Processor section
- A markup result is not displayed
- A Trainer service stopped message is displayed
- Training of an ML model element completed with an error
- The localization language for Help needs to be changed before connecting to the application
- Contacting Technical Support
- Limitations
- Appendix
- Settings of a .env configuration file
- Settings and example of the Excel file containing tag and asset configuration
- Example JSON file containing a preset configuration
- Example JSON file containing a configuration for the Event Processor service
- Viewing the Kaspersky MLAD log
- Special characters of regular expressions
- Cipher suites for secure TLS connection
- Glossary
- Information about third-party code
- Trademark notices
Installing and removing the application > Getting started
Getting started
Getting started
Before starting to work with Kaspersky MLAD, you must make sure that the following conditions are fulfilled:
- The telemetry data source is enabled and configured to send data to Kaspersky MLAD.
- The data transfer network is prepared to deliver telemetry data from the data source to the Kaspersky MLAD server, the network equipment is properly configured, and data transfer is allowed.
- Configuration settings and/or configuration files are prepared for the connector that will be used in Kaspersky MLAD to receive telemetry data or events from external systems. The connector must be configured and activated after Kaspersky MLAD is started.
- Descriptions of tags of received telemetry and assets of the hierarchical structure are prepared as a XLSX file to be imported into Kaspersky MLAD. A description of the presets is supplied in the form of a file in JSON format. The files are created by a qualified technical specialist of the Customer, a Kaspersky specialist or a certified integrator.
- One or more ML models have been created, trained on historical telemetry data. The ML models are prepared for import into Kaspersky MLAD as TAR files if the files were created by a Kaspersky specialist or a certified integrator within the scope of the Kaspersky MLAD Model-building and Deployment Service.
- The Kaspersky MLAD system administrator has been sent the codes for activating ML models. The ML model activation codes are stored in a secure storage location.
Article ID: 247991, Last review: Dec 6, 2023