Hidden policy conditional attribute-based keyword search in federated learning framework

Key Points

• The study uncovers a novel keyword search mechanism that enhances privacy in data retrieval processes.
• Key findings reveal significant improvements in data decentralization and secure sharing across federated learning frameworks.
• Assessment using a federated learning framework demonstrates how conditional attributes can streamline effective keyword searches, ensuring data privacy.
• This approach may enable stronger privacy measures in decentralized data environments, but further validation is needed.