Black box aggressive defense system and method based on neural network interlayer regularization
A neural network and defense system technology, applied in biological neural network models, neural learning methods, neural architectures, etc., can solve problems such as difficult access to training data sets, inability to make progress, and affect black-box attack efficiency, etc., to achieve migration Effects of poor quality, enhanced transferability, and robustness to adversarial training
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[0032] The present invention will be further described below in conjunction with the accompanying drawings. Embodiments of the present invention include, but are not limited to, the following examples.
[0033] A black-box attack defense system based on the regularization of the middle layer of the neural network, including:
[0034] The first source model adopts the ResNet network based on the residual module. In this embodiment, the first source model uses a white-box attack method to attack, and finally outputs the first adversarial sample sequence. Taking the input original picture as an example, input A set of original pictures, using the white box attack method to add appropriate adversarial perturbation to attack the first source model, generate the first adversarial sample sequence, the first adversarial sample sequence also has a certain degree of migration, but for the second source model In other words, because the decision-making direction of the first adversarial...
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