差分隐私GAN梯度裁剪阈值的自适应选取方法

doi:10.11959/j.issn.2096-109x.2018041

Abstract

Abstract:

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:

TP309

Peng GUO, Shangping ZHONG, Kaizhi CHEN, Hang CHENG. Adaptive selection method of differential privacy GAN gradient clipping thresholds[J]. Chinese Journal of Network and Information Security, 2018, 4(5): 10-20.

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数据集	类型	数量	(ε,δ)	分数
	真实数据	60 000	—	9.96±0.03
Mnist	ACGAN生成数据	60 000	—	6.59±0.03
	DPACGAN生成数据	60 000	(4,10^?5)	9.0±0.03
	本文方法生成数据	60 000	(4,10^?5)	7.76±0.03
	真实数据	50 000	—	11.24±0.12
Cifar10	ACGAN生成数据	50 000	—	8.25±0.07
	DPACGAN生成数据	50 000	(8,10^?5)	6.68±0.06
	本文方法生成数据	50 000	(8,10^?5)	7.25±0.07

Adaptive selection method of differential privacy GAN gradient clipping thresholds

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