Malicious actor detection for a virtual conference service

A computing device, comprising:

• one or more memories;
• and
• one or more processors in communication with the one or more memories and configured to execute instructions stored in the one or more memories to perform operations comprising:
• joining, by the computing device, a virtual conference with one or more conference participants, wherein the virtual conference is hosted by a virtual conference provider;
• accessing, by the computing device, conference information corresponding to the virtual conference and participant information corresponding to each of the one or more conference participants;
• providing, by the computing device, the conference information and the participant information as input to a first machine learning model, wherein the first machine learning model is trained to assign a confidence score to each of the one or more conference participants;
• receiving, by the computing device, one or more confidence scores as output from the first machine learning model, wherein each confidence score corresponds to a conference participant;
• and
• determining, by the computing device and for at least one of the one or more conference participants, whether to perform a corrective action on a respective conference participant based on a respective confidence score of the one or more confidence scores.

A non-transitory computer-readable medium storing a plurality of instructions that, when executed by one or more processors of a computing device, cause the one or more processors to perform operations comprising:

• joining, by the computing device, a virtual conference with one or more conference participants, wherein the virtual conference is hosted by a virtual conference provider;
• accessing, by the computing device, conference information corresponding to the virtual conference and participant information corresponding to each of the one or more conference participants;
• providing, by the computing device, the conference information and the participant information as input to a first machine learning model, wherein the first machine learning model is trained to assign a confidence score to each of the one or more conference participants;
• receiving, by the computing device, one or more confidence scores as output from the first machine learning model, wherein each confidence score corresponds to a conference participant;
• and
• determining, by the computing device and for at least one of the one or more conference participants, whether to perform a corrective action on a respective conference participant based on a respective confidence score of the one or more confidence scores.