Graph convolutional network gradient-based node information hiding method

Abstract

The invention discloses a graph convolutional network gradient-based node information hiding method. The method comprises the steps of (1) constructing a network graph, constructing an adjacent matrixaccording to a connected edge set corresponding to the network graph, and preprocessing the adjacent matrix; (2) constructing and training a graph convolutional network model, and determining final weight information of the graph convolutional network model; (3) according to the final weight information, building an objective function based on a goal of ensuring non-target node classification tobe accurate as far as possible and enabling target node classification to be wrong, and calculating a connected edge gradient matrix corresponding to the adjacent matrix by utilizing the objective function; (4) according to a set gradient threshold, symbolizing the connected edge gradient matrix to obtain a connected edge gradient symbol matrix; and (5) updating the adjacent matrix by utilizing the connected edge gradient symbol matrix to hide node information. According to the method, the target node information of a network can be hidden under the condition of slightly changing the structureof the network as far as possible.

Description

technical field [0001] The invention belongs to the technical field of deep learning security, and in particular relates to a node information hiding method based on graph convolution network gradients. Background technique [0002] With the rapid development of science and technology, people use the Internet to browse, shop and other behaviors are becoming more and more common. In the era of artificial intelligence, the behavior and habits of the masses will serve as an important source of information, and various hidden information of the masses can be extracted after in-depth information processing. On the one hand, the extracted hidden information can provide richer and more detailed materials for the academic field and promote the development of academics; on the other hand, the extracted hidden information can improve the service effect of service objects such as stores to the masses. [0003] However, with the deepening of information mining, many scholars have found...

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Problems solved by technology

[0003] However, with the deepening of information mining, many scholars have found that information security is also a very important issue. Excessive collection and mining of user information will cause user information leakage, especially the information protection of target users.

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