Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 1
254-258

Research on physical adversarial sample detection method based on attention mechanism

Wei Zhongcheng1a,2
Feng Hao1a,2
Zhang Xinqiu1a,2
Lian Bin1b,2
1. a. School of Information & Electrical Engineering, b. School of Water Conservancy & Hydroelectric Power, Hebei University of Engineering, Handan Hebei 056038, China
2. Hebei Key Laboratory of Security & Protection Information Sensing & Processing, Handan Hebei 056038, China
DOI: 10.19734/j.issn.1001-3695.2021.06.0255

Abstract

With the popularity and development of deep learning, the existence of adversarial samples is a serious threat to the security of the deep learning model. For the attack problem of adversarial samples in the physical world, this paper proposed a physical adversarial sample detection method based on attention mechanism. The method combined attention mechanism and feature compression to detect pertinently of local visual adversarial samples, excluded effects of non-major regions, and reduced calculation effort. It effectively combined multiple feature compression methods to deal with the main areas of the sample, which destroyed the structure of the antagonistic block and made them unaggressive. Perform defense tests on different adversarial attacked on the MNIST and CIFAR-10 data sets and compared with other countermeasures. The experimental results show that the defense accuracy of the method can reach more than 95%. This method is higher versatility and stronger stability than other local adversarial sample defense methods, and can effectively defense the attack of local visual adversarial samples.

Foundation Support

国家重点研发计划项目(2018YFF0301004)
国家自然科学基金资助项目(61802107)
河北省自然科学基金资助项目(F2018402251)
河北省高等学校科学技术研究项目(QN2020193)
石家庄市重点研发计划项目(201790571A)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.06.0255
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Technology of Information Security
Pages: 254-258
Serial Number: 1001-3695(2022)01-045-0254-05

Publish History

[2021-11-13] Accepted Paper
[2022-01-05] Printed Article

Cite This Article

魏忠诚, 冯浩, 张新秋, 等. 基于注意力机制的物理对抗样本检测方法研究 [J]. 计算机应用研究, 2022, 39 (1): 254-258. (Wei Zhongcheng, Feng Hao, Zhang Xinqiu, et al. Research on physical adversarial sample detection method based on attention mechanism [J]. Application Research of Computers, 2022, 39 (1): 254-258. )

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.

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