Chinese Journal of Network and Information Security ›› 2018, Vol. 4 ›› Issue (5): 10-20.doi: 10.11959/j.issn.2096-109x.2018041

• Papers • Previous Articles     Next Articles

Adaptive selection method of differential privacy GAN gradient clipping thresholds

Peng GUO1,2,Shangping ZHONG1,2,Kaizhi CHEN1,2,Hang CHENG1,2   

  1. 1 College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350116,China
    2 Network System Information Security Fujian Provincial University Key Laboratory,Fuzhou 350116,China
  • Revised:2018-04-02 Online:2018-05-15 Published:2018-08-04
  • Supported by:
    The Natural Science Foundation of Fujian Province(2017J01502);The Scientific Research Foundation of Fuzhou University(XRC-17015)


A method of adaptive selection of differential privacy GAN gradient clipping threshold was proposed.The method assumes that a small portion of public data that is identically distributed with the private data can be accessed,a batch of data is randomly selected from the public data,a clipping threshold is set as an average gradient norm of the batch of data,and the above operations are iterated until the network converges.The method was verified on the Mnist and Cifar10 data sets.The results show that under a reasonable privacy budget,the accuracy of CNN classifiers is improved by 1%~4% compared with the differential privacy auxiliary classifier GAN,inception scores increased by 0.6~1.2.

Key words: GAN, differential privacy protection, gradient clipping thresholds, adaptive selection

CLC Number: 

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