System and method for utilizing large language models and natural language processing technologies to pre-process and analyze data to improve detection of cyber threats

A cybersecurity system, comprising:

• a first large language model (LLM) configured, upon execution, to generate one or more structured elements that operate as a complex filter for automatically extracting salient data from data received from one or more external sources for training of one or more Artificial Intelligence (AI) models;
• a second LLM configured, upon execution, to correlate multiple user credentials associated with different platforms to a common user to enhance training of the one or more AI models formerly trained with data associated with the common user as identified by a first user credential with additional data associated with a second user credential to enhance cyber threat analytics pertaining to activities by the common user;
• a third LLM configured, upon execution, to anonymize at least personally identifiable information (PII) data prior to training of the one or more AI models;
• and
• where instructions implemented in software for the first LLM, the second LLM, and the third LLM are configured to be stored in one or more non-transitory storage mediums to be executed by one or more processing units.

A non-transitory storage medium including one or more large language models configured, when processed by one or more processors, to perform operations comprising:

• generating a first embedding vector based on content within a first data set, wherein the first data set includes at least a first user credential;
• generating a second embedding vector based on content within a second data set, wherein the second data set includes at least a second user credential;
• based on a level of correlation between the first embedding vector and the second embedding vector exceeding a prescribed value, identifying a user is associated with both the first user credential and the second user credential;
• and
• training an Artificial Intelligence (AI) model using both the content within the first data set and the content within the second data set to improve detection of cyber threats associated with data pertaining to the user.