| Neural Network-based Graph Embedding for Cross-Platform Binary Code Similarity Detection X Xu, C Liu, Q Feng, H Yin, L Song, D Song Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications …, 2017 | 400 | 2017 |
| SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning X Xu, C Liu, D Song arXiv preprint arXiv:1711.04436, 2017 | 266 | 2017 |
| Detecting AI trojans using meta neural analysis X Xu, Q Wang, H Li, N Borisov, CA Gunter, B Li 2021 IEEE Symposium on Security and Privacy (SP), 103-120, 2021 | 81 | 2021 |
| QEBA: Query-Efficient Boundary-Based Blackbox Attack H Li, X Xu, X Zhang, S Yang, B Li Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 55 | 2020 |
| RAB: Provable Robustness Against Backdoor Attacks M Weber, X Xu, B Karlas, C Zhang, B Li arXiv preprint arXiv:2003.08904, 2020 | 49 | 2020 |
| A Neural Stochastic Volatility Model R Luo, W Zhang, X Xu, J Wang AAAI 2018, 2017 | 47 | 2017 |
| Fooling Vision and Language Models Despite Localization and Attention Mechanism X Xu, X Chen, C Liu, A Rohrbach, T Darrell, D Song Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 40 | 2018 |
| Can you fool AI with adversarial examples on a visual Turing test? X Xu, X Chen, C Liu, A Rohrbach, T Darell, D Song arXiv preprint arXiv:1709.08693, 2017 | 37 | 2017 |
| A Machine Learning Approach To Prevent Malicious Calls Over Telephony Networks H Li, X Xu, C Liu, T Ren, K Wu, X Cao, W Zhang, Y Yu, D Song 2018 IEEE Symposium on Security and Privacy (SP), 53-69, 2018 | 35 | 2018 |
| Provable robust learning based on transformation-specific smoothing L Li, M Weber, X Xu, L Rimanic, T Xie, C Zhang, B Li arXiv preprint arXiv:2002.12398 4, 2020 | 12 | 2020 |
| Tss: Transformation-specific smoothing for robustness certification L Li, M Weber, X Xu, L Rimanic, B Kailkhura, T Xie, C Zhang, B Li Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications …, 2021 | 10 | 2021 |
| On the Certified Robustness for Ensemble Models and Beyond Z Yang, L Li, X Xu, B Kailkhura, T Xie, B Li arXiv preprint arXiv:2107.10873, 2021 | 8 | 2021 |
| TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness Z Yang, L Li, X Xu, S Zuo, Q Chen, P Zhou, B Rubinstein, C Zhang, B Li Advances in Neural Information Processing Systems 34, 2021 | 6 | 2021 |
| TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness Z Yang, L Li, X Xu, S Zuo, Q Chen, B Rubinstein, C Zhang, B Li arXiv preprint arXiv:2104.00671, 2021 | 6 | 2021 |
| Nonlinear Projection Based Gradient Estimation for Query Efficient Blackbox Attacks H Li, L Li, X Xu, X Zhang, S Yang, B Li International Conference on Artificial Intelligence and Statistics, 3142-3150, 2021 | 5 | 2021 |
| EDoG: Adversarial Edge Detection For Graph Neural Networks X Xu, Y Yu, L Song, C Liu, B Kailkhura, C Gunter, B Li Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2020 | 2 | 2020 |
| Nonlinear Gradient Estimation for Query Efficient Blackbox Attack H Li, L Li, X Xu, X Zhang, S Yang, B Li International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021 | 1 | 2021 |
| Characterizing Adversarial Transferability via Gradient Orthogonality and Smoothness Z Yang, L Li, X Xu, S Zuo, Q Chen, B Rubinstein, C Zhang, B Li ICML 2020 Workshop on Uncertainty and Robustness in Deep Learnin, 2020 | 1 | 2020 |
| Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization X Xu, JY Zhang, E Ma, D Son, O Koyejo, B Li arXiv preprint arXiv:2202.01832, 2022 | | 2022 |
Bo LiUniversity of Illinois at Urbana–ChampaignVerified email at illinois.edu
