| DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems L Ma, F Juefei-Xu, F Zhang, J Sun, M Xue, B Li, C Chen, T Su, L Li, Y Liu, ... arXiv preprint arXiv:1803.07519, 2018 | 779 | 2018 |
| Deephunter: a coverage-guided fuzz testing framework for deep neural networks X Xie, L Ma, F Juefei-Xu, M Xue, H Chen, Y Liu, J Zhao, B Li, J Yin, S See Proceedings of the 28th ACM SIGSOFT international symposium on software …, 2019 | 463 | 2019 |
| Deepmutation: Mutation testing of deep learning systems L Ma, F Zhang, J Sun, M Xue, B Li, F Juefei-Xu, C Xie, L Li, Y Liu, J Zhao, ... 2018 IEEE 29th international symposium on software reliability engineering …, 2018 | 434 | 2018 |
| Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization S Li, M Xue, BZH Zhao, H Zhu, X Zhang arXiv preprint arXiv:1909.02742, 2020 | 330 | 2020 |
| Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach S Chen, M Xue, L Fan, S Hao, L Xu, H Zhu, B Li computers & security 73, 326-344, 2018 | 248 | 2018 |
| Stormdroid: A streaminglized machine learning-based system for detecting android malware S Chen, M Xue, Z Tang, L Xu, H Zhu Proceedings of the 11th ACM on Asia conference on computer and …, 2016 | 206 | 2016 |
| Deepct: Tomographic combinatorial testing for deep learning systems L Ma, F Juefei-Xu, M Xue, B Li, L Li, Y Liu, J Zhao 2019 IEEE 26th International Conference on Software Analysis, Evolution and …, 2019 | 199 | 2019 |
| Hidden backdoors in human-centric language models S Li, H Liu, T Dong, BZH Zhao, M Xue, H Zhu, J Lu Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 151 | 2021 |
| An Empirical Assessment of Global COVID-19 Contact Tracing Applications R Sun, W Wang, M Xue, G Tyson, S Camtepe, D Ranasinghe arXiv preprint arXiv:2006.10933, 2020 | 125* | 2020 |
| Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet Inference X Feng, R Sun, X Zhu, M Xue, S Wen, D Liu, S Nepal, Y Xiang arXiv preprint arXiv:2105.05445, 2021 | 119 | 2021 |
| An Empirical Assessment of Security Risks of Global Android Banking Apps S Chen, L Fan, G Meng, T Su, M Xue, Y Xue, Y Liu, L Xu ACM ICSE 2020, 2020 | 93* | 2020 |
| Combinatorial testing for deep learning systems L Ma, F Zhang, M Xue, B Li, Y Liu, J Zhao, Y Wang arXiv preprint arXiv:1806.07723, 2018 | 89 | 2018 |
| Differentially Private Data Generative Models Q Chen, C Xiang, M Xue, B Li, N Borisov, MA Kaafar, H Zhu http://arxiv.org/abs/1812.02274, 2018 | 85 | 2018 |
| Invisible Backdoor Attacks on Deep Neural Networks via Steganography and Regularization S Li, M Xue, BZH Zhao, H Zhu, X Zhang arXiv preprint arXiv:1909.02742, 2019 | 81 | 2019 |
| Are Mobile Banking Apps Secure? What Can Be Improved? S Chen, T Su, L Fan, G Meng, M Xue, Y Liu, L Xu In Proceedings of the 26th ACM Joint European Software Engineering …, 2018 | 80 | 2018 |
| Data hiding with deep learning: A survey unifying digital watermarking and steganography Z Wang, O Byrnes, H Wang, R Sun, C Ma, H Chen, Q Wu, M Xue IEEE Transactions on Computational Social Systems 10 (6), 2985-2999, 2023 | 73 | 2023 |
| Smoke Screener or Straight Shooter: Detecting Elite Sybil Attacks in User-Review Social Networks H Zheng, M Xue, H Lu, S Hao, H Zhu, X Liang, K Ross Proceedings of Internet Society Symposium on Network and Distributed System …, 2018 | 72 | 2018 |
| Fingerprinting deep neural networks globally via universal adversarial perturbations Z Peng, S Li, G Chen, C Zhang, H Zhu, M Xue Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 71 | 2022 |
| Explainability-based Backdoor Attacks Against Graph Neural Networks J Xu, M Xue, S Picek arXiv preprint arXiv:2104.03674, 2021 | 71 | 2021 |
| The" Beatrix''Resurrections: Robust Backdoor Detection via Gram Matrices W Ma, D Wang, R Sun, M Xue, S Wen, Y Xiang arXiv preprint arXiv:2209.11715, 2022 | 68 | 2022 |
Keith RossProfessor of Computer Science, NYU Abu DhabiGeverifieerd e-mailadres voor nyu.edu