Internet of things malware knowledge extractor and detector

A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:

• training an artificial intelligence (AI) model on data related to malware that may infect internet of things (IoT) devices communicating on a mobility network;
• receiving, from the AI model, information about malware affecting the IoT devices;
• conducting a dialog with the AI model to develop additional information about the malware affecting the IoT devices, wherein the conducting the dialog with the AI model comprises providing textual questions to the AI model and receiving textual answers to the textual questions from the AI model;
• and
• providing, to a device operator associated with the IoT devices, diagnostic information about a malware threat to IoT devices in the mobility network and prescriptive information that may be used to avoid the malware threat, wherein the diagnostic information and the prescriptive information are based on the dialog with the AI model.

A method, comprising:

• receiving, by a processing system including a processor, operational data for Internet of Things (IoT) devices communicating on a mobility network, wherein the IoT devices are associated with a device operator;
• providing, by the processing system, at least some of the operational data to a large language model (LLM), the LLM trained on information about malware in IoT devices;
• receiving, by the processing system, from the LLM, information about a malware risk to the IoT devices;
• receiving, by the processing system, additional malware risk information from the LLM, wherein the receiving the additional malware risk information is based on queries submitted to the LLM about the malware risk to the IoT devices;
• and
• providing, by the processing system to the device operator, diagnostic information about the malware risk to the IoT devices and prescriptive information that may be used to avoid the malware risk to the IoT devices.