| Adversarial learning targeting deep neural network classification: A comprehensive review of defenses against attacks DJ Miller, Z Xiang, G Kesidis Proceedings of the IEEE 108 (3), 402-433, 2020 | 247 | 2020 |
| A Backdoor Attack against 3D Point Cloud Classifiers Z Xiang, DJ Miller, S Chen, X Li, G Kesidis ICCV 2021, 2021 | 67 | 2021 |
| Detection of backdoors in trained classifiers without access to the training set Z Xiang, DJ Miller, G Kesidis IEEE Transactions on Neural Networks and Learning Systems, 2020 | 57 | 2020 |
| A benchmark study of backdoor data poisoning defenses for deep neural network classifiers and a novel defense Z Xiang, DJ Miller, G Kesidis 2019 IEEE 29th International Workshop on Machine Learning for Signal …, 2019 | 54 | 2019 |
| Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios Z Xiang, DJ Miller, G Kesidis ICLR 2022, 2022 | 48 | 2022 |
| Revealing backdoors, post-training, in DNN classifiers via novel inference on optimized perturbations inducing group misclassification Z Xiang, DJ Miller, G Kesidis ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 37 | 2020 |
| MM-BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic H Wang, Z Xiang, DJ Miller, G Kesidis IEEE Symposium on Security & Privacy, 2024 | 22* | 2024 |
| Detecting scene-plausible perceptible backdoors in trained DNNs without access to the training set Z Xiang, DJ Miller, H Wang, G Kesidis Neural computation 33 (5), 1329-1371, 2021 | 22* | 2021 |
| Reverse engineering imperceptible backdoor attacks on deep neural networks for detection and training set cleansing Z Xiang, DJ Miller, G Kesidis Computers & Security 106, 102280, 2021 | 21 | 2021 |
| BadChain: Backdoor chain-of-thought prompting for large language models Z Xiang, F Jiang, Z Xiong, B Ramasubramanian, R Poovendran, B Li ICLR 2024, 2024 | 18 | 2024 |
| L-red: Efficient post-training detection of imperceptible backdoor attacks without access to the training set Z Xiang, DJ Miller, G Kesidis ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 18 | 2021 |
| Detecting backdoor attacks against point cloud classifiers Z Xiang, DJ Miller, S Chen, X Li, G Kesidis ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 17 | 2022 |
| Artprompt: Ascii art-based jailbreak attacks against aligned llms F Jiang, Z Xu, L Niu, Z Xiang, B Ramasubramanian, B Li, R Poovendran arXiv preprint arXiv:2402.11753, 2024 | 16 | 2024 |
| Test-time detection of backdoor triggers for poisoned deep neural networks X Li, Z Xiang, DJ Miller, G Kesidis ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 14 | 2022 |
| UMD: Unsupervised Model Detection for X2X Backdoor Attacks Z Xiang, Z Xiong, B Li Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 9 | 2023 |
| Revealing perceptible backdoors in DNNs, without the training set, via the maximum achievable misclassification fraction statistic Z Xiang, DJ Miller, H Wang, G Kesidis 2020 IEEE 30th International Workshop on Machine Learning for Signal …, 2020 | 8 | 2020 |
| A scalable mixture model based defense against data poisoning attacks on classifiers X Li, DJ Miller, Z Xiang, G Kesidis Dynamic Data Driven Applications Systems: Third International Conference …, 2020 | 6 | 2020 |
| Training set cleansing of backdoor poisoning by self-supervised representation learning H Wang, S Karami, O Dia, H Ritter, E Emamjomeh-Zadeh, J Chen, ... ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 5 | 2023 |
| Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time Detection H Wang, Z Xiang, DJ Miller, G Kesidis arXiv preprint arXiv:2308.04617, 2023 | 4 | 2023 |
| Malicious agent detection for robust multi-agent collaborative perception Y Zhao, Z Xiang, S Yin, X Pang, S Chen, Y Wang International Conference on Intelligent Robots and Systems (IROS 2024), 2023 | 3 | 2023 |
George KesidisProfessor of Computer Science and Engineering, Pennsylvania State University; Professor of Electrical Engineering, Pennsylvania 在 engr.psu.edu 的电子邮件经过验证
