Image recognition system and method based on blockchain and federated learning

Abstract

The invention provides an image recognition system and method based on a blockchain and federated learning, and belongs to the technical field of industrial Internet of Things, and the system comprises a model construction module and an image recognition module. In the Internet of Things image recognition process, an image collaborative recognition mechanism based on a blockchain and federated learning is provided, firstly, a set of credible collaborative mechanism is established between distributed Internet of Things devices which are not credible mutually by introducing the blockchain, and distributed image collaborative recognition is achieved; secondly, by utilizing a federated learning algorithm, an image recognition model is jointly learned among distributed Internet of Things equipment, so that centralized transmission of original data is avoided; and finally, by using the global model trained by federal learning, the Internet of Things equipment can quickly and efficiently complete an image recognition task locally, and accurate image recognition is realized while the data privacy is ensured.

Description

technical field [0001] The invention belongs to the technical field of industrial internet of things, and in particular relates to an image recognition system and method based on blockchain and federated learning. Background technique [0002] In real life, except for a few giant companies that can meet the requirements, most enterprises have the problem of small amount of data and poor data quality, which is not enough to support the realization of artificial intelligence technology; at the same time, domestic and foreign regulatory environments are gradually strengthening data protection, and successively introduced Therefore, the free flow of data under the premise of security and compliance has become the general trend; from the perspective of users and enterprises, the data owned by commercial companies often has huge potential value, and the two companies and even departments between companies must Considering the exchange of interests, these institutions often do not ...

AI Technical Summary

Problems solved by technology

[0004](1) Lack of trust among various participants: In the IoT scenario, the data monitored by each sensor device is closely related to the user, especially the image data It is relatively sensitive. Due to the lack of mutual trust among various participants, it is difficult to establish a credible collaboration mechanism to effectively analyze and utilize image data

[0005](2) Large-scale centralized training data is required: current image recognition algorithms based on machine learning such as neural networks and deep learning require a large amount of image data as training sets , to ensure the accuracy of the model, and in the Internet of Things, due to the limitation of resources such as device storage, it is difficult to centrally provide large-scale training data

[0006](3) The security and privacy of training data is difficult to guarantee: Since the training data will contain sensitive information of users, it may be subject to malicious attacks and face serious data leakage threats. Once these sensitive data are leaked, it will cause serious losses to IoT users.

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