Algorithm Research & Explore
|
2009-2012

Privacy-preserving deep learning training data generation scheme

Tang Fengyi
Liu Jian
Wang Huimei
Xian Ming
College of Electronic Science & Technology, National University of Defense Technology, Changsha 410000, China

Abstract

The deep learning model training has some problems such as lack of large amount of labeled training data and data privacy leakage. To solve these problems, this paper proposed a conditional generative adversarial network(CGAN) based on deep learning model training data generation scheme. By virtue of the characteristics that CGAN could generate sufficient amount of labeled training data with the same distribution of real data, this scheme used CGAN combined with data morphing to satisfy the requirements of large amount of labeled training data generation and data privacy protection simultaneously. Experimental results show that the scheme is efficient and feasible, and it has advantages in data availability and data privacy preservation when compared with other schemes.

Foundation Support

国家自然科学基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.10.0360
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 7
Section: Algorithm Research & Explore
Pages: 2009-2012
Serial Number: 1001-3695(2021)07-017-2009-04

Publish History

[2021-07-05] Printed Article

Cite This Article

汤凤仪, 刘建, 王会梅, 等. 保护数据隐私的深度学习训练数据生成方案 [J]. 计算机应用研究, 2021, 38 (7): 2009-2012. (Tang Fengyi, Liu Jian, Wang Huimei, et al. Privacy-preserving deep learning training data generation scheme [J]. Application Research of Computers, 2021, 38 (7): 2009-2012. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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