Systems and methods for secure transport and processing of data in federated learning

A first user equipment (UE), comprising:

• one or more processors configured to:
• identify a configuration that includes artificial intelligence or machine learning (AI/ML) model parameters to be used and shared for federated learning;
• generate an AI/ML model based on the configuration, wherein the AI/ML model is based on an anonymization and encryption of one or more information elements (IEs) using policy information;
• establish a circle-of-trust to include the first UE and a second UE;
• and
• transmit the AI/ML model to the second UE based on the second UE being included in the circle-of-trust.

A non-transitory computer-readable medium storing a set of instructions, the set of instructions comprising:

• one or more instructions that, when executed by one or more processors of a first user equipment (UE), cause the first UE to:
• identify a configuration that includes artificial intelligence or machine learning (AI/ML) model parameters to be used and shared for federated learning;
• generate an AI/ML model based on the configuration, wherein the AI/ML model is based on an anonymization and encryption of one or more information elements (IEs) using policy information;
• establish a circle-of-trust to include the first UE and a second UE;
• and
• transmit the AI/ML model to the second UE based on the second UE being included in the circle-of-trust.