System and method for secure knowledge distillation using homomorphic encryption in machine learning environments

A non-transitory computer-readable medium storing a set of instructions for secure knowledge transfer between machine learning models, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a device, cause the device to:
• determine whether a local language model within a secure environment is capable of processing an input query based on one or more criteria;
• generate a response using the local language model when the local language model is determined to be capable of processing the query;
• generate an external processing request when the local language model is determined to be not capable of processing the query;
• perform, within the secure environment, retrieval augmented generation to generate an enhanced query using information from a private database, wherein at least a portion of the enhanced query is included in the external processing request ;
• encrypt the external processing request using a homomorphic encryption technique;
• transmit the encrypted external processing request to an external environment;
• receive an encrypted response from the external environment;
• decrypt the encrypted response within the secure environment to generate a decrypted response;
• perform knowledge distillation on the decrypted response to extract knowledge patterns;
• and
• update the local language model using the extracted knowledge patterns.

A system for secure knowledge transfer between machine learning models comprising:

• a processing circuitry;
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• determine whether a local language model within a secure environment is capable of processing an input query based on one or more criteria;
• generate a response using the local language model when the local language model is determined to be capable of processing the query;
• generate an external processing request when the local language model is determined to be not capable of processing the query;
• perform, within the secure environment, retrieval augmented generation to generate an enhanced query using information from a private database, wherein at least a portion of the enhanced query is included in the external processing request ;
• encrypt the external processing request using a homomorphic encryption technique;
• transmit the encrypted external processing request to an external environment;
• receive an encrypted response from the external environment;
• decrypt the encrypted response within the secure environment to generate a decrypted response;
• perform knowledge distillation on the decrypted response to extract knowledge patterns;
• and
• update the local language model using the extracted knowledge patterns.