Papers on “adversarial robustness”

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Research on “adversarial robustness” in the 480 tracked journals: papers per year and category, the journals, institutions and countries publishing it, the keywords studied with it and its most-cited papers. It is not among the most frequent keywords of the last 30 days, so this page has no list of its latest papers. Also as Markdown.

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Key findings#

From 2017 to 2026 (so far), the keyword “adversarial robustness” appeared in 740 papers in the tracked journals, most of them in AI (669), information systems (56) and operations research (10).
155 of them were published in 2025, against 4 in 2017.
Since 2023, the institutions with the most of these papers were Chinese Academy of Sciences (28), Tsinghua University (18) and Harbin Institute of Technology (16).
The journals publishing most of them were Neural Networks (53), Pattern Recognition (51) and IEEE Transactions on Pattern Analysis and Machine Intelligence (50).
The most-cited of them is “Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization” (International Journal of Computer Vision, 2019), with 6,898 citations.

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2017	2018	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	3	1	10	27	42	80	84	122	143	157
Information Systems	0	0	2	3	3	11	15	10	6	6
Operations Research	1	0	0	0	0	1	1	2	4	1
Statistics	0	0	0	0	0	0	0	1	2	1
Higher Education and Research	0	0	0	0	0	0	0	0	0	1
All categories	4	1	12	30	45	92	100	135	155	166

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Neural Networks	53
2	Pattern Recognition	51
3	IEEE Transactions on Pattern Analysis and Machine Intelligence	50
4	Expert Systems with Applications	49
5	Information Sciences	36
6	Computers & Security	36
7	IEEE Transactions on Neural Networks and Learning Systems	34
8	Knowledge-Based Systems	33
9	Neural Computing and Applications	24
10	International Journal of Computer Vision	23

Institutions with the most papers, since 2023
#	Institution	Papers
1	Chinese Academy of Sciences	28
2	Tsinghua University	18
3	Harbin Institute of Technology	16
4	Nanyang Technological University	16
5	South China University of Technology	16
6	Beihang University	15
7	National University of Defense Technology	15
8	Peng Cheng Laboratory	15
9	University of Chinese Academy of Sciences	15
10	Sichuan University	14

Countries with the most papers, since 2023
#	Country	Papers
1	China	350
2	United States	62
3	United Kingdom	42
4	Australia	33
5	Hong Kong	32
6	Singapore	32
7	Italy	25
8	India	23
9	South Korea	21
10	Germany	17

Keywords with the most papers, since 2023
#	Keyword	Papers
1	adversarial training	107
2	adversarial attacks	106
3	adversarial examples	71
4	black-box attacks	53
5	image classification	47
6	deep neural network	39
7	adversarial defense	37
8	backdoor attacks	35
9	graph neural networks	32

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	6,898	81.3	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization	International Journal of Computer Vision	2019-10-11	Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das et al.
2	827	11.9	Salient Object Detection in the Deep Learning Era: An In-Depth Survey	IEEE Transactions on Pattern Analysis and Machine Intelligence	2021-01-13	Wenguan Wang, Qiuxia Lai, Huazhu Fu et al.
3	548	11.5	Privacy and Robustness in Federated Learning: Attacks and Defenses	IEEE Transactions on Neural Networks and Learning Systems	2022-11-10	Lingjuan Lyu, Han Yu, Xingjun Ma et al.
4	506	10.2	Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond	Knowledge and Information Systems	2022-09-14	Xuhong Li, Haoyi Xiong, Xingjian Li et al.
5	288	2.6	Analysis of classifiers’ robustness to adversarial perturbations	Machine Learning	2017-08-25	Alhussein Fawzi, Omar Fawzi, Pascal Frossard B

Cite this page

Scholar4AI. (2026). Papers on “adversarial robustness”. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/keywords/adversarial-robustness

@misc{scholar4ai-keywords-adversarial-robustness,
  author = {{Scholar4AI}},
  title = {Papers on “adversarial robustness”},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/keywords/adversarial-robustness}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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