Li, Y.Z.[Yue-Zun],
Chang, M.C.[Ming-Ching],
Sun, P.[Pu],
Qi, H.G.[Hong-Gang],
Dong, J.Y.[Jun-Yu],
Lyu, S.W.[Si-Wei],
TransRPN: Towards the Transferable Adversarial Perturbations using
Region Proposal Networks and Beyond,
CVIU(213), 2021, pp. 103302.
Elsevier DOI
2112
Transferable adversarial perturbation, Object detection
BibRef
Gao, L.L.[Lian-Li],
Huang, Z.J.[Zi-Jie],
Song, J.K.[Jing-Kuan],
Yang, Y.[Yang],
Shen, H.T.[Heng Tao],
Push & Pull: Transferable Adversarial Examples With Attentive
Attack,
MultMed(24), 2022, pp. 2329-2338.
IEEE DOI
2205
Perturbation methods, Feature extraction, Computational modeling,
Task analysis, Predictive models, Neural networks,
targeted attack
BibRef
Zhang, S.H.[Shi-Hui],
Zuo, D.X.[Dong-Xu],
Yang, Y.L.[Yong-Liang],
Zhang, X.W.[Xiao-Wei],
A Transferable Adversarial Belief Attack With Salient Region
Perturbation Restriction,
MultMed(25), 2023, pp. 4296-4306.
IEEE DOI
2310
BibRef
Khedr, Y.M.[Yasmeen M.],
Liu, X.[Xin],
He, K.[Kun],
TransMix: Crafting highly transferable adversarial examples to evade
face recognition models,
IVC(146), 2024, pp. 105022.
Elsevier DOI
2405
Adversarial examples, Attack transferability,
Face verification, Data augmentation, Black-box attack
BibRef
Lu, Y.T.[Yan-Tao],
Liu, N.[Ning],
Li, Y.[Yilan],
Chen, J.C.[Jin-Chao],
Velipasalar, S.[Senem],
Cross-task and time-aware adversarial attack framework for perception
of autonomous driving,
PR(165), 2025, pp. 111652.
Elsevier DOI
2505
Adversarial examples, Cross-task, Perception, Autonomous driving
BibRef
Lu, Y.T.[Yan-Tao],
Ren, H.N.[Hai-Ning],
Chai, W.H.[Wei-Heng],
Velipasalar, S.[Senem],
Li, Y.[Yilan],
Time-aware and task-transferable adversarial attack for perception of
autonomous vehicles,
PRL(178), 2024, pp. 145-152.
Elsevier DOI
2402
Adversarial attack, Black-box, Perception, Real-time
BibRef
Chen, H.[Hai],
Zhao, S.[Shu],
Yan, Y.[Yuanting],
Qian, F.[Fulan],
Enhancing the Transferability of Adversarial Point Clouds by
Initializing Transferable Adversarial Noise,
SPLetters(32), 2025, pp. 201-205.
IEEE DOI
2501
Point cloud compression, Training, Solid modeling, Analytical models,
Limiting, Noise, Robustness, Generators, Glass box, transferability
BibRef
Peng, X.[Xiyu],
Zhou, J.Y.[Jing-Yi],
Wu, X.F.[Xiao-Feng],
Distillation-Based Cross-Model Transferable Adversarial Attack for
Remote Sensing Image Classification,
RS(17), No. 10, 2025, pp. 1700.
DOI Link
2505
BibRef
Hu, C.[Cong],
He, Z.C.[Zhi-Chao],
Wu, X.J.[Xiao-Jun],
Query-efficient black-box ensemble attack via dynamic surrogate
weighting,
PR(161), 2025, pp. 111263.
Elsevier DOI
2502
Black-box attack, Ensemble strategies, Deep neural networks,
Transferable adversarial example, Image classification
BibRef
Chen, J.Q.[Jian-Qi],
Chen, H.[Hao],
Chen, K.[Keyan],
Zhang, Y.[Yilan],
Zou, Z.X.[Zheng-Xia],
Shi, Z.W.[Zhen-Wei],
Diffusion Models for Imperceptible and Transferable Adversarial
Attack,
PAMI(47), No. 2, February 2025, pp. 961-977.
IEEE DOI
2501
Diffusion models, Perturbation methods, Closed box,
Noise reduction, Solid modeling, Image color analysis, Glass box,
transferable attack
BibRef
Liu, J.L.[Jun-Lin],
Lyu, X.C.[Xin-Chen],
Ren, C.[Chenshan],
Cui, Q.[Qimei],
Crafting More Transferable Adversarial Examples via Quality-Aware
Transformation Combination,
MultMed(27), 2025, pp. 7917-7929.
IEEE DOI
2510
Robustness, Training, Probability distribution,
Diversity reception, Splines (mathematics), Perturbation methods,
adversarial transferability
BibRef
Zhao, Z.Y.[Zheng-Yu],
Zhang, H.W.[Han-Wei],
Li, R.[Renjue],
Sicre, R.[Ronan],
Amsaleg, L.[Laurent],
Backes, M.[Michael],
Li, Q.[Qi],
Wang, Q.[Qian],
Shen, C.[Chao],
Revisiting Transferable Adversarial Images:
Systemization, Evaluation, and New Insights,
PAMI(48), No. 1, January 2026, pp. 765-780.
IEEE DOI
2512
Security.
Biological system modeling, Systematics, Perturbation methods,
Machine learning, Training, Pipelines, Guidelines, Closed box,
attack stealthiness
BibRef
Wei, X.X.[Xing-Xing],
Ruan, S.[Shouwei],
Dong, Y.P.[Yin-Peng],
Su, H.[Hang],
Cao, X.C.[Xiao-Chun],
Distributionally Location-Aware Transferable Adversarial Patches for
Facial Images,
PAMI(47), No. 4, April 2025, pp. 2849-2864.
IEEE DOI
2503
Face recognition, Optimization, Closed box, Robustness,
Visualization, Perturbation methods, Computational modeling,
transfer-based attack
BibRef
Wang, H.Q.[Hong-Qiang],
Lan, Y.Q.[Yu-Qing],
Yue, F.Z.[Fu-Zhan],
Xia, Z.H.[Zheng-Huan],
Zhang, T.[Tao],
BUM: Bayesian Uncertainty Minimization for Transferable Adversarial
Examples in SAR Recognition,
RS(18), No. 5, 2026, pp. 693.
DOI Link
2603
BibRef
Zhang, H.[Han],
Huang, B.Q.[Bo-Qi],
Wang, B.S.[Bing-Shu],
Zhang, L.X.[Lai-Xian],
Shangguan, A.[Aihong],
Zhang, H.[Haosu],
DPSF: A Dynamic Patch Shape Selection Framework for Cross-Model
Transferable Adversarial Attacks,
RS(18), No. 14, 2026, pp. 2426.
DOI Link
2608
BibRef
Fang, Z.W.[Zheng-Wei],
Wang, R.[Rui],
Huang, T.[Tao],
Jing, L.P.[Li-Ping],
Strong Transferable Adversarial Attacks via Ensembled Asymptotically
Normal Distribution Learning,
CVPR24(24841-24850)
IEEE DOI
2410
Deep learning, Image transformation, Perturbation methods,
Computational modeling, Stochastic processes,
Stochastic gradient descent
BibRef
Zhang, J.P.[Jian-Ping],
Huang, Y.Z.[Yi-Zhan],
Wu, W.B.[Wei-Bin],
Lyu, M.R.[Michael R.],
Transferable Adversarial Attacks on Vision Transformers with Token
Gradient Regularization,
CVPR23(16415-16424)
IEEE DOI
2309
BibRef
Ma, W.S.[Wen-Shuo],
Li, Y.D.[Yi-Dong],
Jia, X.F.[Xiao-Feng],
Xu, W.[Wei],
Transferable Adversarial Attack for Both Vision Transformers and
Convolutional Networks via Momentum Integrated Gradients,
ICCV23(4607-4616)
IEEE DOI
2401
BibRef
Wu, T.[Tao],
Luo, T.[Tie],
Wunsch, D.C.[Donald C.],
GNP Attack: Transferable Adversarial Examples Via Gradient Norm
Penalty,
ICIP23(3110-3114)
IEEE DOI
2312
BibRef
Lin, Z.[Zhi],
Peng, A.J.[An-Jie],
Wei, R.[Rong],
Yu, W.X.[Wen-Xin],
Zeng, H.[Hui],
An Enhanced Transferable Adversarial Attack of Scale-Invariant
Methods,
ICIP22(3788-3792)
IEEE DOI
2211
Convolution, Convolutional neural networks,
convolution neural network, adversarial examples, transferability
BibRef
Son, M.J.[Min-Ji],
Kwon, M.J.[Myung-Joon],
Kim, H.S.[Hee-Seon],
Byun, J.[Junyoung],
Cho, S.[Seungju],
Kim, C.[Changick],
Adaptive Warping Network for Transferable Adversarial Attacks,
ICIP22(3056-3060)
IEEE DOI
2211
Deep learning, Adaptation models, Adaptive systems,
Perturbation methods, Neural networks, Search problems, Warping
BibRef
Wang, Z.B.[Zhi-Bo],
Guo, H.C.[Heng-Chang],
Zhang, Z.F.[Zhi-Fei],
Liu, W.X.[Wen-Xin],
Qin, Z.[Zhan],
Ren, K.[Kui],
Feature Importance-aware Transferable Adversarial Attacks,
ICCV21(7619-7628)
IEEE DOI
2203
Degradation, Limiting, Correlation, Computational modeling,
Aggregates, Transforms, Adversarial learning, Explainable AI,
Recognition and classification
BibRef
Zheng, H.,
Zhang, Z.,
Gu, J.,
Lee, H.,
Prakash, A.,
Efficient Adversarial Training With Transferable Adversarial Examples,
CVPR20(1178-1187)
IEEE DOI
2008
Training, Perturbation methods, Robustness, Computational modeling,
Measurement, Iterative methods, Silicon
BibRef
Dong, Y.P.[Yin-Peng],
Pang, T.Y.[Tian-Yu],
Su, H.[Hang],
Zhu, J.[Jun],
Evading Defenses to Transferable Adversarial Examples by
Translation-Invariant Attacks,
CVPR19(4307-4316).
IEEE DOI
2002
BibRef
Inkawhich, N.[Nathan],
Wen, W.[Wei],
Li, H.(.[Hai (Helen)],
Chen, Y.R.[Yi-Ran],
Feature Space Perturbations Yield More Transferable Adversarial
Examples,
CVPR19(7059-7067).
IEEE DOI
2002
BibRef
Zhou, W.[Wen],
Hou, X.[Xin],
Chen, Y.J.[Yong-Jun],
Tang, M.Y.[Meng-Yun],
Huang, X.Q.[Xiang-Qi],
Gan, X.[Xiang],
Yang, Y.[Yong],
Transferable Adversarial Perturbations,
ECCV18(XIV: 471-486).
Springer DOI
1810
BibRef
Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Backdoor Attacks .