Outsourcing convolutional neural network privacy protection system based on secure two-party calculation

A privacy protection system and convolutional neural network technology, applied in the field of information security, can solve the problems of inability to protect complex neural network model parameters, privacy leakage, etc.

Active Publication Date: 2020-06-23
WUHAN UNIV
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Problems solved by technology

However, service outsourcing is accompanied by the risk of privacy leakage. Existing protection schemes can only protect query data and prediction results from being leaked, but cannot protect the parameters of complex neural network models.

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  • Outsourcing convolutional neural network privacy protection system based on secure two-party calculation
  • Outsourcing convolutional neural network privacy protection system based on secure two-party calculation
  • Outsourcing convolutional neural network privacy protection system based on secure two-party calculation

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Embodiment Construction

[0054] Below in conjunction with accompanying drawing and specific embodiment the present invention will be described in further detail:

[0055] In recent years, along with the upsurge of artificial intelligence, deep learning technology has gradually emerged and affected many fields of computer science. Its powerful predictive ability makes the prediction service of neural network model an indispensable part of many current business activities. This has led to the application of neural network forecasting service outsourcing. Because these neural network models have important value, how to protect the neural network models deployed on external servers has also become an important research direction. This system uses two servers that will not collude with each other. This assumption is often used in the research of security outsourcing, and it is the most basic security guarantee for service outsourcing. At the same time, the system uses highly secure technologies such as ho...

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Abstract

The invention discloses an outsourcing convolutional neural network privacy protection system based on secure two-party calculation, which randomly allocates a neural network and query data to two servers which are not communicated with each other, and realizes image processing through cooperative operation on the two servers. The two image components are input into two servers; information transmitted between servers is hidden in a convolution layer by using triples of random data. A confusion circuit is designed on an active layer to realize a ReLU function, then dimensionality reduction ofan image is carried out through average pooling, finally, two components of a prediction result are obtained through a full connection layer adopting triple hidden information, and the two componentsare returned to a user to be combined to obtain the obtained prediction result. In order to improve the calculation efficiency, an asynchronous calculation method and a parallel query method are adopted, independent calculations in the same query are carried out at the same time, and different parts of a plurality of queries are processed at the same time, so that the time of each query is greatlyreduced.

Description

technical field [0001] The invention belongs to the technical field of information security, and in particular relates to a privacy-protected neural network outsourcing method and system based on secure two-party computing. Background technique [0002] With breakthroughs in the field of deep learning, neural networks have demonstrated powerful advantages over previous techniques in terms of predictive capabilities. Among a variety of neural network models, convolutional neural networks stand out due to their good performance, and have been widely used in medical image analysis, natural language processing, and text recognition. For cost considerations, some service providers will deploy the model to an external server and provide subsequent prediction services. However, service outsourcing is accompanied by the risk of privacy leakage. Existing protection schemes can only protect query data and prediction results from being leaked, but cannot protect the parameters of comp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F21/14G06N3/04
CPCG06F21/14G06N3/045
Inventor 王骞牟宁平李明慧胡胜山李琦沈超
Owner WUHAN UNIV
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