Publications
I'm interested in Computer Vision, Federated Learning, and AI Security. Currently, most of my research is about Novel View Synthesis and AI Security.
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Feature Distraction Based Backdoor Defense for Federated Trained Intrusion Detection System
Yu-Wen Chen*,
Bo-Hsu Ke*,
Yen-Xin Wang,
Shih-Heng Lin,
Ming-Han Tsai,
Bo-Zhong Chen,
Jian-Jhih Kuo*,
Ren-Hung Hwang
IEEE Global Communications Conference, (GLOBECOM), 2024
source code
This paper proposes a novel defense framework called FDDF (Features Distraction Defense Framework) to mitigate trigger backdoor attacks in federated learning-based intrusion detection systems by identifying and eliminating the most significant features that may contain triggers, without interfering with the model training process.
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Knowledge Distillation Based Defense for Audio Trigger Backdoor in Federated Learning
Yu-Wen Chen*,
Bo-Hsu Ke*,
Bo-Zhong Chen*,
Si-Rong Chiu,
Chun-Wei Tu,
Jian-Jhih Kuo*
IEEE Global Communications Conference, (GLOBECOM), 2023
source code
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paper
We propose the Knowledge Distillation Defense Framework (KDDF) to detect and remove features of the potential triggers during the inference. KDDF utilizes Knowledge Distillation (KD) to train a validation model on each IoT device, which is used to identify suspicious data.
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Successive Interference Cancellation Based Defense for Trigger Backdoor in Federated Learning
Yu-Wen Chen*,
Bo-Hsu Ke*,
Bo-Zhong Chen*,
Si-Rong Chiu,
Chun-Wei Tu,
Jian-Jhih Kuo*
IEEE International Conference on Communications, (ICC), 2023
source code
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paper
This paper proposes a Successive Interference Cancellation-based Defense Framework (SICDF) to detect and eliminate the trigger during model inference.
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Stolen from Jon Barron's website.
Last updated Sep 2024.
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