In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
Algorithm Research & Explore
|
764-769

Algorithm for defense adversarial example based on adaptive noise addition

Liu Ye
Huang Xianying
Liu Wenxing
Zhu Xiaofei
Li Zhaoping
School of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China

Abstract

Deep neural networks are vulnerable to the attack of adversarial examples. To solve this problem, some works trained networks by adding Gaussian noise to the image, thereby improving the ability of the network to defend adversarial examples. But the method did not consider the sensitivity of the network to different areas in the image when adding noise. To solve this problem, this paper proposed an adversarial training algorithm based on gradient guidance noise addition. When training the network, it added adaptive noise to different areas based on the sensitivity, added large noise to the more sensitive areas, suppressed the sensitivity of the network to image changes, added less noise to the less sensitive areas and improved the network classification accuracy. Compared with the existing algorithms on the Cifar-10 dataset, the experimental results show that the proposed method effectively improves the accuracy of neural networks when classifying adversarial examples.

Foundation Support

国家自然科学基金资助项目
重庆市基础科学与前沿技术研究重点专项资助项目(cstc2017jcyjBX0059)
重庆市巴南区科技计划资助项目(2018TJ05)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.03.0055
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: Algorithm Research & Explore
Pages: 764-769
Serial Number: 1001-3695(2021)03-024-0764-06

Publish History

[2021-03-05] Printed Article

Cite This Article

刘野, 黄贤英, 刘文星, 等. 基于自适应噪声添加的防御对抗样本算法 [J]. 计算机应用研究, 2021, 38 (3): 764-769. (Liu Ye, Huang Xianying, Liu Wenxing, et al. Algorithm for defense adversarial example based on adaptive noise addition [J]. Application Research of Computers, 2021, 38 (3): 764-769. )

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.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)