A CMA-ES-Based Adversarial Attack on Black-Box Deep Neural Networks Article Swipe
Xiaohui Kuang
,
Hongyi Liu
,
Ye Wang
,
Qikun Zhang
,
Quanxin Zhang
,
Jun Zheng
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2956553
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/access.2019.2956553
Deep neural networks(DNNs) are widely used in AI-controlled Cyber-Physical Systems (CPS) to controll cars, robotics, water treatment plants and railways. However, DNNs have vulnerabilities to well-designed input samples that are called adversarial examples. Adversary attack is one of the important techniques for detecting and improving the security of neural networks. Existing attacks, including state-of-the-art black-box attack have a lower success rate and make invalid queries that are not beneficial to obtain the direction of generating adversarial examples. For these reasons, this paper proposed a CMA-ES-based adversarial attack on black-box DNNs. Firstly, an efficient method to reduce the number of invalid queries is introduced. Secondly, a black-box attack of generating adversarial examples to fit a high-dimensional independent Gaussian distribution of the local solution space is proposed. Finally, a new CMA-based perturbation compression method is applied to make the process of reducing perturbation smoother. Experimental results on ImageNet classifiers show that the proposed attack has a higher success-rate than the state-of-the-art black-box attack but reduce the number of queries by 30% equally.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2019.2956553
- https://ieeexplore.ieee.org/ielx7/6287639/8600701/08917642.pdf
- OA Status
- gold
- Cited By
- 7
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2993234371
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2993234371Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2019.2956553Digital Object Identifier
- Title
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A CMA-ES-Based Adversarial Attack on Black-Box Deep Neural NetworksWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-01-01Full publication date if available
- Authors
-
Xiaohui Kuang, Hongyi Liu, Ye Wang, Qikun Zhang, Quanxin Zhang, Jun ZhengList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2019.2956553Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/8600701/08917642.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/8600701/08917642.pdfDirect OA link when available
- Concepts
-
Adversarial system, Computer science, Deep neural networks, Black box, Adversary, Artificial neural network, Artificial intelligence, Machine learning, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2023: 2, 2021: 2, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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47Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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