Query sequence obfuscation using large language model generation of decoy topics

A computer program product comprising:

• one or more computer-readable storage media;
• and
• program instructions stored on the one or more computer-readable storage media to perform operations comprising:
• receiving a user search query sequence comprising at least one pairing of a first user search query and a second user search query that is subsequent to the first user search query in the user search query sequence;
• generating, for the pairing, a difference vector between a vector embedding of the second user search query and a vector embedding of the first user search query;
• and
• applying the difference vector to a vector embedding of a previous decoy search query to generate a subsequent decoy search query in a decoy search query sequence, wherein the vector embeddings of the first user search query, second user search query, and the previous decoy search query are generated by a large language model (LLM) based on a semantic embedding space associated with the LLM.

A computer system comprising:

• a processor set;
• one or more computer-readable storage media;
• and
• program instructions stored on the one or more computer-readable storage media to cause the processor set to perform operations comprising:
• receiving a user search query sequence comprising at least one pairing of a first user search query and a second user search query that is subsequent to the first user search query in the user search query sequence;
• generating, for the pairing, a difference vector between a vector embedding of the second user search query and a vector embedding of the first user search query;
• and
• applying the difference vector to a vector embedding of a previous decoy search query to generate a subsequent decoy search query in a decoy search query sequence, wherein the vector embeddings of the first user search query, second user search query, and the previous decoy search query are generated by a large language model (LLM) based on a semantic embedding space associated with the LLM.