Abstract:
An industrial control system hardened against malicious activity monitors highly dynamic control data to develop a dynamic thumbprint that can be evaluated to detect deviations from normal behavior of a type that suggest tampering or other attacks. Evaluation of the dynamic thumbprint may employ a set of ranges defining normal operation and reflecting known patterns of interrelationship between dynamic variables.
Abstract:
An industrial control system hardened against malicious activity monitors highly dynamic control data to develop a dynamic thumbprint that can be evaluated to detect deviations from normal behavior of a type that suggest tampering or other attacks. Evaluation of the dynamic thumbprint may employ a set of ranges defining normal operation and reflecting known patterns of interrelationship between dynamic variables.
Abstract:
An industrial control system providing security against tampering or modification generates periodic state thumbprints defining a state of control elements that may be forwarded to a security or safety appliance for comparison to a benchmark thumbprint indicating no tampering. The transmitted state thumbprint may capture not only programs but also configuration and environmental states of the control element.
Abstract:
An industrial controller resistant to malicious attacks may provide a graduated response employing the elements of the control system to reduce access to the control system, log data, and announce intrusion based on a dynamically evolving assessment of the severity of any detected security issues.
Abstract:
An industrial control system providing security against tampering or modification generates periodic state thumbprints defining a state of control elements that may be forwarded to a security or safety appliance for comparison to a benchmark thumbprint indicating no tampering. The transmitted state thumbprint may capture not only programs but also configuration and environmental states of the control element.
Abstract:
For displaying a node of a tree structure, a processor receives an anchor node creation command for a given node of a tree structure of nodes. The given node has one or more branches of parent nodes. The processor further removes the one or more branches of parent nodes and branches of sibling nodes of the given node from a display of the tree structure. In addition, the processor displays the given node as a topmost node of the tree structure.
Abstract:
The present technology relates to artificial intelligence assisted device configuration. In an implementation, an interface service of a device design application receives an input comprising an association between a device and a controller of an automation system design. The interface service then generates a first prompt requesting an application type associated with the device. The interface service next transmits the first prompt to a large language model and receives a first response to the first prompt from the large language model, wherein the first response includes the application type. The interface service then generates a second prompt requesting configuration settings for the device based on the system information and the application type. The interface service next transmits the second prompt to the large language model and receives a second response to the second prompt that includes configuration settings for the device. The interface service then displays the second response.
Abstract:
Technology disclosed herein includes a prompt engineering service that integrates artificial intelligence with the programming systems of an industrial automation environment to design a system of the industrial automation environment. The interface service leverages the capabilities of a large language model (LLM) trained on industrial automation workflows to provide accurate and relevant system design information. For example, the interface service receives system configuration data and generates a first prompt requesting a category associated with the system configuration data. The interface service uses the first prompt to generate a response from the LLM. The interface service generates a second prompt requesting a user interface message for offering assistance to configure the system based on the category. The interface service uses the second prompt to generate the user interface message and displays the message in a user interface.
Abstract:
The present technology relates to artificial intelligence assisted device troubleshooting. In an implementation, an interface service of a human machine interface application trains a machine learning model on the content of an embeddings database. The interface service then receives an input comprising a context of an automation system design. The interface service generates a prompt that includes an instruction for the ML model to identify an anomaly type associated with the context of the automation system design and to generate a solution that addresses the anomaly type. The interface service transmits the prompt to the ML model and receives a response from the ML model that includes the anomaly type and the requested solution. After receiving a response, the interface service may modify the automation system design based on the content of the response and surface a graphical user interface that includes the modified design.
Abstract:
For displaying a node of a tree structure, a processor receives an anchor node creation command for a given node of a tree structure of nodes. The given node has one or more branches of parent nodes. The processor further removes the one or more branches of parent nodes and branches of sibling nodes of the given node from a display of the tree structure. In addition, the processor displays the given node as a topmost node of the tree structure.