Towards Evaluating the Robustness of Neural Networks

Cited by (1,019)

Items 701–800 of 1,019

1. (De)Randomized Smoothing for Certifiable Defense against Patch Attacks
   Alexander Levine, Soheil Feizi · 2020 · arXiv (Cornell University)
2. To be Robust or to be Fair: Towards Fairness in Adversarial Training
   Han Xu, Xiaorui Liu, Li, Yaxin, Anil K. Jain, Jiliang Tang · 2020 · arXiv (Cornell University)
3. POBA-GA: Perturbation optimized black-box adversarial attacks via genetic algorithm
   Jinyin Chen, Mengmeng Su, Shijing Shen, Hui Xiong, Haibin Zheng · 2019 · Computers & Security
4. Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction
   Yantao Lu, Yunhan Jia, Jianyu Wang, Bai Li, Weiheng Chai, Lawrence Carin, Senem Velipasalar · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
5. On the Robustness of Face Recognition Algorithms Against Attacks and Bias
   Richa Singh, Akshay Agarwal, Maneet Singh, Shruti Nagpal, Mayank Vatsa A · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
6. A Data Augmentation-Based Defense Method Against Adversarial Attacks in Neural Networks
   Yi Zeng, Han Qiu, Gérard Memmi, Meikang Qiu A · 2020 · Lecture notes in computer science
7. Benchmarking the Robustness of Semantic Segmentation Models with Respect to Common Corruptions
   Christoph Kamann, Carsten Rother · 2020 · International Journal of Computer Vision
8. Towards a physical-world adversarial patch for blinding object detection models
   Yajie Wang, Haoran Lv, Xiaohui Kuang, Gang Zhao, Yu‐an Tan, Quanxin Zhang, Jingjing Hu · 2020 · Information Sciences
9. Adversarial Patch Attack on Multi-Scale Object Detection for UAV Remote Sensing Images
   Yichuang Zhang, Yu Zhang, Jiahao Qi, Kangcheng Bin, Hao Wen, Xunqian Tong, Ping Zhong · 2022 · Remote Sensing
10. AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
    Yulong Cao, Chaowei Xiao, Animashree Anandkumar, Danfei Xu, Marco Pavone · 2022 · Lecture notes in computer science
11. A Survey on Convolutional Neural Networks and Their Performance Limitations in Image Recognition Tasks
    Gabriela Rangel, Juan Carlos Cuevas-Tello, Jose Ignacio Nunez-Varela, Cesar Puente, Alejandra Guadalupe Silva Trujillo · 2024 · Journal of Sensors
12. Adversarial attack and defense strategies for deep speaker recognition systems
    Arindam Jati, Chin-Cheng Hsu, Monisankha Pal, Raghuveer Peri, Wael AbdAlmageed, Shrikanth Narayanan · 2021 · Computer Speech & Language
13. Gotta Catch'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
    Shawn Shan, Emily Wenger, Bolun Wang, Bo Li, Hai-Tao Zheng, Ben Y. Zhao · 2020 · ACM SIGSAC Conference on Computer and Communications Security (CCS)
14. Testing Robustness Against Unforeseen Adversaries
    Kaufmann, Max, Daniel D. Kang, Yi Jie Sun, Basart, Steven, Yin, Xuwang, Mazeika, Mantas, Arora, Akul, Dziedzic, Adam, Boenisch, Franziska, Brown, Tom et al. · 2019 · arXiv (Cornell University)
15. Hermes Attack: Steal DNN Models with Lossless Inference Accuracy
    Yuankun Zhu, Yueqiang Cheng, Husheng Zhou, Yantao Lu · 2020 · arXiv (Cornell University)
16. An adversarial attack on DNN-based black-box object detectors
    Yajie Wang, Yu‐an Tan, Wenjiao Zhang, Yuhang Zhao, Xiaohui Kuang · 2020 · Journal of Network and Computer Applications
17. Efficient Adversarial Attacks for Visual Object Tracking
    Siyuan Liang, Xingxing Wei, Siyuan Yao, Xiaochun Cao · 2020 · Lecture notes in computer science
18. Data-free Universal Adversarial Perturbation and Black-box Attack
    Chaoning Zhang, Philipp Benz, Adil Karjauv, In So Kweon · 2021 · IEEE/CVF International Conference on Computer Vision (ICCV)
19. Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
    Wenqi Wei, Ling Liu · 2024 · ACM Computing Surveys
20. Adversarial Challenges in Network Intrusion Detection Systems: Research Insights and Future Prospects
    Sabrine Ennaji, Fabio De Gaspari, Dorjan Hitaj, Alicia K Bidi, Luigi Vincenzo Mancini · 2025 · IEEE Access
21. Selective Audio Adversarial Example in Evasion Attack on Speech Recognition System
    Hyun Kwon, Yongchul Kim, Hyunsoo Yoon, Daeseon Choi · 2019 · IEEE Transactions on Information Forensics and Security
22. Targeted Mismatch Adversarial Attack: Query With a Flower to Retrieve the Tower
    Giorgos Tolias, Filip Radenović, Ondřej Chum · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
23. Invisible Mask: Practical Attacks on Face Recognition with Infrared
    Zhe Guang Zhou, Di Tang, Xiaofeng Wang, Weili Han, Xiangyu Liu, Kehuan Zhang · 2018 · arXiv (Cornell University)
24. DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
    Huanrui Yang, Jingyang Zhang, Hongliang Dong, Nathan Inkawhich, Gardner, Andrew, Andrew Touchet, Wesley Wilkes, Heath Berry, Hai Helen Li · 2020 · arXiv (Cornell University)
25. Throwing Darts in the Dark? Detecting Bots with Limited Data using Neural Data Augmentation
    Steve T. K. Jan, Qingying Hao, Tianrui Hu, Jiameng Pu, Sonal Oswal, Gang Wang, Bimal Viswanath · 2020 · IEEE Symposium on Security and Privacy (S&P)
26. Toward Secure and Efficient Deep Learning Inference in Dependable IoT Systems
    Han Qiu, Qinkai Zheng, Tianwei Zhang, Meikang Qiu A, Gérard Memmi, Jialiang Lu · 2020 · IEEE Internet of Things Journal
27. Query-Efficient Black-Box Adversarial Attack With Customized Iteration and Sampling
    Yucheng Shi, Yahong Han, Qinghua Hu, Yi Yang, Qi Chuan Tian · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
28. Towards Efficient Data Free Blackbox Adversarial Attack
    Jie Zhang, Bo Li, Jianghe Xu, Shuang Wu, Shouhong Ding, Lei Zhang, Chao Wu · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
29. A comprehensive evaluation framework for deep model robustness
    Jun Guo, Wei Bao, Jiakai Wang, Yuqing Ma, Xinghai Gao, Gang Xiao, Aishan Liu, Jian Dong, Xianglong Liu, Wenjun Wu · 2023 · Pattern Recognition
30. Audio-deepfake detection: Adversarial attacks and countermeasures
    Mouna Rabhi, Spiridon Bakiras, Roberto Di Pietro · 2024 · Expert Systems with Applications
31. A Review of Federated Learning Applications in Intrusion Detection Systems
    Aitor Belenguer, Jose Antonio Pascual, Javier Navaridas · 2025 · Computer Networks
32. Forgotten Siblings: Unifying Attacks on Machine Learning and Digital Watermarking
    Erwin Quiring, Daniel Arp, Konrad Rieck · 2018 · IEEE European Symposium on Security and Privacy
33. Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Convolutional Networks
    Kenneth T. Co, Luis Muñoz-González, Sixte de Maupeou, Emil C. Lupu · 2019 · ACM SIGSAC Conference on Computer and Communications Security (CCS)
34. Survey: Leakage and Privacy at Inference Time
    Jegorova, Marija, Kaul, Chaitanya, Mayor, Charlie, O'Neil, Alison Q., Weir, Alexander, Murray-Smith, Roderick, Tsaftaris, Sotirios A. · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
35. Boosting Fast Adversarial Training With Learnable Adversarial Initialization
    Jia, Xiaojun, Zhang, Yong, Wu, Baoyuan, Wang, Jue, Cao, Xiaochun · 2022 · IEEE Transactions on Image Processing
36. Adversarial Examples in RF Deep Learning: Detection and Physical Robustness
    Silvija Kokalj-Filipović, Rob Miller, Garrett Vanhoy · 2019 · IEEE Global Conference on Signal and Information Processing
37. Latent space data assimilation by using deep learning
    Mathis Peyron, Anthony Fillion, Selime Gürol, Victor Marchais, Serge Gratton, Pierre Boudier, Gaël Goret · 2021 · Quarterly Journal of the Royal Meteorological Society
38. Graph Adversarial Attack via Rewiring
    Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang · 2021 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
39. Detecting Deep-Fake Videos from Aural and Oral Dynamics
    Shruti Agarwal, Hany Farid · 2021 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
40. Delving into Data: Effectively Substitute Training for Black-box Attack
    Wenxuan Wang, Bangjie Yin, Taiping Yao, Li Zhang, Yanwei Fu, Shouhong Ding, Jilin Li, Feiyue Huang, Xiangyang Xue · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
41. Exploring Adversarial Attack in Spiking Neural Networks With Spike-Compatible Gradient
    Ling Liang, Xing Hu, Lei Deng, Yujie Wu, Guoqi Li, Yufei Ding, Peng Li, Yuan Xie · 2021 · IEEE Transactions on Neural Networks and Learning Systems
42. A survey of identity recognition via data fusion and feature learning
    Zhen Qin, Pengbiao Zhao, Tianming Zhuang, Fuhu Deng, Yi Ding, Da-Jiang Chen · 2022 · Information Fusion
43. AdvDiffuser: Natural Adversarial Example Synthesis with Diffusion Models
    Xinquan Chen, Xitong Gao, Juanjuan Zhao, Kejiang Ye, Chengzhong Xu · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
44. Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders
    Partha Sarathi Ghosh, Arpan Losalka, Michael J. Black · 2019 · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))
45. Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems
    Kexin Pei, Zhu, Linjie, Yinzhi Cao, Junfeng Yang, Carl Vondrick, Suman Jana · 2017 · arXiv (Cornell University)
46. Instance adaptive adversarial training: Improved accuracy tradeoffs in neural nets
    Y. Balaji, T. Goldstein, Judy Hoffman · 2019 · arXiv.org
47. MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
    Runtian Zhai, Dan Chen, Di He, Huan Zhang, Boqing Gong, Pradeep Ravikumar, Cho‐Jui Hsieh, Liwei Wang · 2020 · arXiv (Cornell University)
48. On Success and Simplicity: A Second Look at Transferable Targeted Attacks
    Zhengyu Zhao, Zhuoran Liu, Martha Larson · 2020 · arXiv (Cornell University)
49. A Framework for Enhancing Deep Neural Networks Against Adversarial Malware
    Deqiang Li, Qianmu Li, Yanfang Ye, Shouhuai Xu · 2021 · IEEE Transactions on Network Science and Engineering
50. Towards Inspecting and Eliminating Trojan Backdoors in Deep Neural Networks
    Wenbo Guo, Lun Wang, Yan Hui Xu, Xinyu Xing, Min Du, Dawn Xiaodong Song · 2020 · Proceedings
51. RobOT: Robustness-Oriented Testing for Deep Learning Systems
    Jingyi Wang, Jialuo Chen, Youcheng Sun, Xingjun Ma, Dongxia Wang, Jun Sun, Peng Cheng · 2021 · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
52. Simulating Unknown Target Models for Query-Efficient Black-box Attacks
    Chen Ma, Li Chen, Jun‐Hai Yong · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
53. Defense Against Adversarial Attacks by Reconstructing Images
    Shudong Zhang, Haichang Gao, Qingxun Rao · 2021 · IEEE Transactions on Image Processing
54. Enhancing MR image segmentation with realistic adversarial data augmentation
    Chen Chen, Chen Qin, Cheng Ouyang, Zeju Li, Shuo Wang, Huaqi Qiu, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert · 2022 · Medical Image Analysis
55. DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks
    D. Gopinath, Guy Katz, C. Păsăreanu, Clark W. Barrett · 2017 · arXiv.org
56. Misleading Authorship Attribution of Source Code using Adversarial Learning
    Erwin Quiring, Alwin Maier, Konrad Rieck · 2019 · arXiv (Cornell University)
57. Toward Interpretable Machine Learning: Transparent Deep Neural Networks and Beyond
    Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Christopher J. Anders, Klaus‐Robert Müller · 2020 · arXiv (Cornell University)
58. Unlearnable Examples: Making Personal Data Unexploitable
    Hanxun Huang, Xingjun Ma, Sarah Erfani, James Bailey, Yisen Wang · 2021 · arXiv (Cornell University)
59. DL2: Training and Querying Neural Networks with Logic.
    Marc Fischer, Mislav Balunović, Dana Drachsler-Cohen, Timon Gehr, Ce Zhang, Martin Vechev · 2019 · International Conference on Machine Learning
60. Trust Region Based Adversarial Attack on Neural Networks
    Zhewei Yao, Amir Gholami, Peng Xu, Kurt Keutzer, Michael W. Mahoney · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
61. Towards Robust Image Classification Using Sequential Attention Models
    Daniel Zoran, Mike Chrzanowski, Po-Sen Huang, Sven Gowal, A. Mott, Pushmeet Kohli · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
62. Effective white-box testing of deep neural networks with adaptive neuron-selection strategy
    Seokhyun Lee, Sooyoung Cha, Dain Lee, Hakjoo Oh · 2020 · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
63. Block-Wise Image Transformation With Secret Key for Adversarially Robust Defense
    AprilPyone MaungMaung, Hitoshi Kiya · 2021 · IEEE Transactions on Information Forensics and Security
64. A survey on adversarial attacks and defenses for object detection and their applications in autonomous vehicles
    Abdollah Amirkhani, Mohammad Parsa Karimi, Amin Banitalebi-Dehkordi · 2022 · The Visual Computer
65. An Empirical Survey on Explainable AI Technologies: Recent Trends, Use-Cases, and Categories from Technical and Application Perspectives
    Mohammad Nagahisarchoghaei, Nasheen Nur, Logan Cummins, Nashtarin Nur, Mirhossein Mousavi Karimi, Shreya Nandanwar, Siddhartha Bhattacharyya, Shahram Rahimi · 2023 · Electronics
66. Boosting Adversarial Transferability via Gradient Relevance Attack
    Hegui Zhu, Yuchen Ren, Xiaoyan Sui, Lianping Yang, Wuming Jiang · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
67. Adversarial machine learning: a review of methods, tools, and critical industry sectors
    Sotiris Pelekis, Thanos Koutroubas, Afroditi Blika, Anastasis Berdelis, Evangelos Karakolis, Christos Ntanos, Evangelos Spiliotis, Dimitris Askounis · 2025 · Artificial Intelligence Review
68. Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation
    Alexander Levine, Soheil Feizi · 2020 · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))
69. Universal adversarial perturbations against object detection
    Debang Li, Junge Zhang, Kaiqi Huang · 2020 · Pattern Recognition
70. Tiny noise, big mistakes: adversarial perturbations induce errors in brain–computer interface spellers
    Xiao Zhang, Dongrui Wu, Lieyun Ding, Hanbin Luo, Chin-Teng Lin, Tzyy‐Ping Jung, Ricardo Chavarriaga · 2020 · National Science Review
71. On the Robustness of Cooperative Multi-Agent Reinforcement Learning
    Jieyu Lin, Kristina Dzeparoska, Sai Qian Zhang, Alberto Leon‐Garcia, Nicolas Papernot · 2020 · IEEE Security and Privacy Workshops (SPW)
72. Exploring misclassifications of robust neural networks to enhance adversarial attacks
    Leo Schwinn, René Raab, An Nguyen, Dario Zanca, Bjoern M. Eskofier · 2023 · Applied Intelligence
73. Poisoning attacks and countermeasures in intelligent networks: Status quo and prospects
    Chen Wang, Jian Chen, Yang Yang, Xiaoqiang Ma, Jiangchuan Liu · 2021 · Digital Communications and Networks
74. A Backdoor Attack against 3D Point Cloud Classifiers
    Zhen James Xiang, David Jonathan Miller, Siheng Chen, Xi Li, George Kesidis · 2021 · IEEE/CVF International Conference on Computer Vision (ICCV)
75. An Approximated Gradient Sign Method Using Differential Evolution for Black-Box Adversarial Attack
    Chao Li, Handing Wang, Jun Zhang, Wen Yao, Tingsong Jiang · 2022 · IEEE Transactions on Evolutionary Computation
76. Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification
    Xixun Lin, Chuan De Zhou, Jia Wu, Hong Tao Yang, Haibo Wang, Yanan Cao, Bin Wang · 2022 · Pattern Recognition
77. 3D-VField: Adversarial Augmentation of Point Clouds for Domain Generalization in 3D Object Detection
    Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Mohammad-Ali Nikouei Mahani, Nassir Navab, Benjamin Busam, Federico Tombari · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
78. Metaverse-IDS: Deep learning-based intrusion detection system for Metaverse-IoT networks
    Tarek Gaber, Joseph Bamidele Awotunde, Mohamed F. Torky, Sunday Adeola Ajagbe, Mohammad Ali A. Hammoudeh, Wei Li · 2023 · Internet of Things
79. Defensive dropout for hardening deep neural networks under adversarial attacks
    Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David R Kaeli, Peter S. Chin, Xue Lin · 2018
80. Targeted Adversarial Examples Against RF Deep Classifiers
    Silvija Kokalj-Filipović, Rob Miller, Joshua Morman · 2019 · ACM Workshop on Wireless Security and Machine Learning (WiseML)
81. Property Inference for Deep Neural Networks
    Divya Gopinath, Hayes Converse, Corina S. Păsăreanu, Ankur Taly · 2019 · IEEE/ACM International Conference on Automated Software Engineering (ASE)
82. FDA$^3$: Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
    Yunfei Song, Tian Liu, Tongquan Wei, Xiangfeng Wang, Zhe Tao, Mingsong Chen · 2020 · IEEE Transactions on Industrial Informatics
83. Adversarial Attack and Defense on Point Sets
    Jiancheng Yang, Qiang Zhang, Rongyao Fang, Bingbing Ni, Jinxian Liu, Qi Chuan Tian · 2019 · arXiv (Cornell University)
84. MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples
    Jia, Jinyuan, Ahmed Salem, Michael Backes A, Y Victoria Zhang, Neil Zhenqiang Gong · 2019 · arXiv (Cornell University)
85. Membership Inference Attacks Against Recommender Systems
    Zhang, Minxing, Ren, Zhaochun, Wang, Zihan, Ren, Pengjie, Chen, Zhunmin, Hu, Pengfei, Zhang, Yang · 2021 · Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security
86. On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method
    Pu Zhao, Sijia Liu, Pin‐Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
87. Detecting numerical bugs in neural network architectures
    Yuhao Zhang, Luyao Ren, Liqian Chen, Yingfei Xiong, Shing-Chi Cheung, Tao Xie · 2020 · ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE)
88. AdvDoor: adversarial backdoor attack of deep learning system
    Quan Zhang, Yifeng Ding, Yongqiang Tian, Jianmin Guo, Min Yuan, Yu Jiang · 2021 · ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
89. SegPGD: An Effective and Efficient Adversarial Attack for Evaluating and Boosting Segmentation Robustness
    Jindong Gu, Hengshuang Zhao, Volker Tresp, Philip H. S. Torr · 2022 · Lecture notes in computer science
90. Deep Learning for Medical Image Cryptography: A Comprehensive Review
    Kusum Lata, Linga Reddy Cenkeramaddi · 2023 · Applied Sciences
91. Batch virtual adversarial training for graph convolutional networks
    Zhijie Deng, Yinpeng Dong, Jun Zhu · 2023 · AI Open
92. Learn2Perturb: An End-to-End Feature Perturbation Learning to Improve Adversarial Robustness
    Ahmadreza Jeddi, Mohammad Javad Shafiee, Michelle E. Karg, Christian Scharfenberger, Alexander K.C. Wong · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
93. Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification
    Linyi Yang, Eoin M. Kenny, Tin Lok James Ng, Yi Yang, Barry Smyth, Ruihai Dong · 2020 · International Conference on Computational Linguistics
94. Maximal Jacobian-based Saliency Map Attack
    Rey Reza Wiyatno, Anqi Xu · 2018 · arXiv (Cornell University)
95. DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems
    Husheng Zhou, Wei Li, Yuankun Zhu, Yuqun Zhang, Bei Yu, Lingming Zhang, Cong Liu · 2018 · arXiv (Cornell University)
96. Enhancing Adversarial Defense by k-Winners-Take-All
    Chang Xiao, Peilin Zhong, Changxi Zheng · 2019 · arXiv (Cornell University)
97. Robustness of Graph Neural Networks at Scale
    Geisler, Simon, Schmidt, Tobias, Hakan Şirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann · 2021 · arXiv (Cornell University)
98. MADE
    Alina Oprea, Zhou Li, Robin Norris, Kevin D. Bowers · 2018 · Annual Computer Security Applications Conference
99. Reciprocal Learning Networks for Human Trajectory Prediction
    Hao Sun, Zhiqun Zhao, Zhihai He · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
100. attackGAN: Adversarial Attack against Black-box IDS using Generative Adversarial Networks
     Shuang Zhao, Jing Li, Jianmin Wang, Zhao Zhang, Lin Zhu, Yong Zhang · 2021 · Procedia Computer Science