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Publication search results
found 66 matches
- 2024
- Chengfang Li, Gaoyun Fang, Yang Liu, Jing Liu, Liang Song:
Decoding Silent Reading EEG Signals Using Adaptive Feature Graph Convolutional Network. IEEE Signal Process. Lett. 31: 1-5 (2024) - 2023
- Qingqing Ye, Haibo Hu, Xiaofeng Meng, Huadi Zheng, Kai Huang, Chengfang Fang, Jie Shi:
PrivKVM*: Revisiting Key-Value Statistics Estimation With Local Differential Privacy. IEEE Trans. Dependable Secur. Comput. 20(1): 17-35 (2023) - Zijun Lin, Ke Xu, Chengfang Fang, Huadi Zheng, Aneez Ahmed Jaheezuddin, Jie Shi:
QUDA: Query-Limited Data-Free Model Extraction. AsiaCCS 2023: 913-924 - Jiyi Zhang, Han Fang, Wesley Joon-Wie Tann, Ke Xu, Chengfang Fang, Ee-Chien Chang:
Mitigating Adversarial Attacks by Distributing Different Copies to Different Buyers. AsiaCCS 2023: 704-715 - Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo:
Certified Robustness of Quantum Classifiers Against Adversarial Examples Through Quantum Noise. ICASSP 2023: 1-5 - Han Fang, Jiyi Zhang, Yupeng Qiu, Jiayang Liu, Ke Xu, Chengfang Fang, Ee-Chien Chang:
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence. ICCV 2023: 4312-4321 - Rong Du, Qingqing Ye, Yue Fu, Haibo Hu, Jin Li, Chengfang Fang, Jie Shi:
Differential Aggregation against General Colluding Attackers. ICDE 2023: 2180-2193 - Maura Pintor, Luca Demetrio, Angelo Sotgiu, Hsiao-Ying Lin, Chengfang Fang, Ambra Demontis, Battista Biggio:
Detecting Attacks Against Deep Reinforcement Learning for Autonomous Driving. ICMLC 2023: 57-62 - Han Fang, Kejiang Chen, Yupeng Qiu, Jiayang Liu, Ke Xu, Chengfang Fang, Weiming Zhang, Ee-Chien Chang:
DeNoL: A Few-Shot-Sample-Based Decoupling Noise Layer for Cross-channel Watermarking Robustness. ACM Multimedia 2023: 7345-7353 - Haoyang Li, Qingqing Ye, Haibo Hu, Jin Li, Leixia Wang, Chengfang Fang, Jie Shi:
3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning. SP 2023: 1893-1907 - Han Fang, Jiyi Zhang, Yupeng Qiu, Ke Xu, Chengfang Fang, Ee-Chien Chang:
Tracing the Origin of Adversarial Attack for Forensic Investigation and Deterrence. CoRR abs/2301.01218 (2023) - Rong Du, Qingqing Ye, Yue Fu, Haibo Hu, Jin Li, Chengfang Fang, Jie Shi:
Differential Aggregation against General Colluding Attackers. CoRR abs/2302.09315 (2023) - Li Wang, Jiaqi Li, Yuhao Luo, Jiahao Zheng, Lei Wang, Hao Li, Ke Xu, Chengfang Fang, Jie Shi, Zhizheng Wu:
AdvSV: An Over-the-Air Adversarial Attack Dataset for Speaker Verification. CoRR abs/2310.05369 (2023) - 2022
- Huadi Zheng, Qingqing Ye, Haibo Hu, Chengfang Fang, Jie Shi:
Protecting Decision Boundary of Machine Learning Model With Differentially Private Perturbation. IEEE Trans. Dependable Secur. Comput. 19(3): 2007-2022 (2022) - Tai-Yue Li, Venugopala Reddy Mekala, Ka-Lok Ng, Cheng-Fang Su:
Classification of Tumor Metastasis Data by Using Quantum kernel-based Algorithms. BIBE 2022: 351-354 - Yaxin Xiao, Qingqing Ye, Haibo Hu, Huadi Zheng, Chengfang Fang, Jie Shi:
MExMI: Pool-based Active Model Extraction Crossover Membership Inference. NeurIPS 2022 - Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo:
Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise. CoRR abs/2211.00887 (2022) - Ambra Demontis, Maura Pintor, Luca Demetrio, Kathrin Grosse, Hsiao-Ying Lin, Chengfang Fang, Battista Biggio, Fabio Roli:
A Survey on Reinforcement Learning Security with Application to Autonomous Driving. CoRR abs/2212.06123 (2022) - 2021
- Tianyu Du, Shouling Ji, Lujia Shen, Yao Zhang, Jinfeng Li, Jie Shi, Chengfang Fang, Jianwei Yin, Raheem Beyah, Ting Wang:
Cert-RNN: Towards Certifying the Robustness of Recurrent Neural Networks. CCS 2021: 516-534 - Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, Ting Wang:
Backdoor Pre-trained Models Can Transfer to All. CCS 2021: 3141-3158 - An Zhang, Xiang Wang, Chengfang Fang, Jie Shi, Tat-Seng Chua, Zehua Chen:
A-FMI: Learning Attributions from Deep Networks via Feature Map Importance. CoRR abs/2104.05527 (2021) - Xinyi Zhang, Chengfang Fang, Jie Shi:
Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack. CoRR abs/2104.05921 (2021) - Lujia Shen, Shouling Ji, Xuhong Zhang, Jinfeng Li, Jing Chen, Jie Shi, Chengfang Fang, Jianwei Yin, Ting Wang:
Backdoor Pre-trained Models Can Transfer to All. CoRR abs/2111.00197 (2021) - 2020
- Chengfang Li, Xiaojie Fang, Xiaokang Zhou, Lin Mei, Xuejun Sha:
Enhanced signalling provisioning for UAV-enabled MEC: A GWFRFT-based energy-spreading transmission approach. IET Commun. 14(15): 2524-2531 (2020) - Ya-Han Hu, Chun-Tien Tai, Kang Ernest Liu, Cheng-Fang Cai:
Identification of highly-cited papers using topic-model-based and bibliometric features: the consideration of keyword popularity. J. Informetrics 14(1): 101004 (2020) - Chang Liao, Yao Cheng, Chengfang Fang, Jie Shi:
Where Does the Robustness Come from?: A Study of the Transformation-based Ensemble Defence. AISec@CCS 2020: 1-12 - Hsiao-Ying Lin, Chengfang Fang, Jie Shi:
Bident Structure for Neural Network Model Protection. ICISSP 2020: 377-384 - Chang Liao, Yao Cheng, Chengfang Fang, Jie Shi:
Where Does the Robustness Come from? A Study of the Transformation-based Ensemble Defence. CoRR abs/2009.13033 (2020) - 2019
- Huadi Zheng, Qingqing Ye, Haibo Hu, Chengfang Fang, Jie Shi:
BDPL: A Boundary Differentially Private Layer Against Machine Learning Model Extraction Attacks. ESORICS (1) 2019: 66-83 - 2018
- Young-Sam Kwon, Ying-Chieh Lin, Cheng-Fang Su:
Derivation of Inviscid Quasi-geostrophic Equation from Rotational Compressible Magnetohydrodynamic Flows. J. Nonlinear Sci. 28(2): 599-620 (2018)
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