Bo Li
Zitiert von
Zitiert von
Robust physical-world attacks on deep learning visual classification
K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, C Xiao, A Prakash, ...
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Targeted backdoor attacks on deep learning systems using data poisoning
X Chen, C Liu, B Li, K Lu, D Song
arXiv preprint arXiv:1712.05526, 2017
Characterizing adversarial subspaces using local intrinsic dimensionality
X Ma, B Li, Y Wang, SM Erfani, S Wijewickrema, G Schoenebeck, D Song, ...
arXiv preprint arXiv:1801.02613, 2018
Generating adversarial examples with adversarial networks
C Xiao, B Li, JY Zhu, W He, M Liu, D Song
arXiv preprint arXiv:1801.02610, 2018
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, ...
Proceedings of the 33rd ACM/IEEE International Conference on Automated …, 2018
Manipulating machine learning: Poisoning attacks and countermeasures for regression learning
M Jagielski, A Oprea, B Biggio, C Liu, C Nita-Rotaru, B Li
2018 IEEE Symposium on Security and Privacy (SP), 19-35, 2018
Spatially transformed adversarial examples
C Xiao, JY Zhu, B Li, W He, M Liu, D Song
arXiv preprint arXiv:1801.02612, 2018
Data poisoning attacks on factorization-based collaborative filtering
B Li, Y Wang, A Singh, Y Vorobeychik
Advances in neural information processing systems, 1885-1893, 2016
Data Poisoning Attacks on Factorization-based Collaborative Filtering
YV B. Li, Y. Wang, A. Singh
In Proceedings of the Neural Information Processing Systems (NIPS), 2016
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
Physical adversarial examples for object detectors
D Song, K Eykholt, I Evtimov, E Fernandes, B Li, A Rahmati, F Tramer, ...
12th {USENIX} Workshop on Offensive Technologies ({WOOT} 18), 2018
Feature cross-substitution in adversarial classification
B Li, Y Vorobeychik
Advances in neural information processing systems, 2087-2095, 2014
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
Orthogonal weight normalization: Solution to optimization over multiple dependent stiefel manifolds in deep neural networks
L Huang, X Liu, B Lang, AW Yu, Y Wang, B Li
arXiv preprint arXiv:1709.06079, 2017
Textbugger: Generating adversarial text against real-world applications
J Li, S Ji, T Du, B Li, T Wang
arXiv preprint arXiv:1812.05271, 2018
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
Practical black-box attacks on deep neural networks using efficient query mechanisms
AN Bhagoji, W He, B Li, D Song
European Conference on Computer Vision, 158-174, 2018
The seventh visual object tracking vot2019 challenge results
M Kristan, J Matas, A Leonardis, M Felsberg, R Pflugfelder, ...
Proceedings of the IEEE International Conference on Computer Vision …, 2019
Optimal randomized classification in adversarial settings.
Y Vorobeychik, B Li
AAMAS, 485-492, 2014
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
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