Multi-source encrypted image retrieval method based on federated learning and secret sharing

US11750377B2 · kind B2 · utility

Assignee

• Nanhu Laboratory · CN

Inventor

• Lei Zhang · Beijing, CN

Key dates

• Filing date: Dec 20, 2022
• Grant date: Sep 5, 2023
• Expiry date: Dec 20, 2042

Classification

• Technology area (CPC Y): Emerging Cross-Sectional Technologies
• CPC primary: Y02D10/00
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Disclosed is a multi-source encrypted image retrieval method based on federated learning and secret sharing, including the following steps: S1. performing model training on a convolutional neural network of double cloud platforms based on federated learning, with an image owner joining the double cloud platforms as a coalition member; and S2. completing, by an authorized user, encrypted image retrieval based on additive secret sharing with the assistance of the double cloud platforms. The present disclosure provides a multi-source encrypted retrieval scheme based on federated learning and secret sharing, which simplifies the neural network model structure for retrieval by using federated learning, to obtain better network parameters. Better neural network parameters and a more simplified network model structure are achieved by compromising overheads on the image owner side, such that a better convolutional neural network can be used in encrypted image retrieval.