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Backdoor attacks have posed a significant threat to the security of deep neural networks (DNNs).
“Long short-term memory,”
Sepp Hochreiter and Jürgen Schmidhuber, · 1997
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Laurens Van der Maaten and Geoffrey Hinton, · 2008
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“Study of automated face recognition system for office door access control application,”
Ratnawati Ibrahim and Zalhan Mohd Zin, · 2011
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“Feature extraction using mfcc,”
Shikha Gupta, Jafreezal Jaafar, WF Wan Ahmad, and Arpit Bansal, · 2013
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“Deepface: Closing the gap to human-level performance in face verification,”
Yaniv Taigman, Ming Yang, Marc’Aurelio Ranzato, and Lior Wolf, · 2014
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“Face recognition methods & applications,”
Divyarajsinh N Parmar and Brijesh B Mehta, · 2014
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“Deep residual learning for image recognition,”
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun, · 2016
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“Targeted backdoor attacks on deep learning systems using data poisoning,”
Xinyun Chen, Chang Liu, Bo Li, Kimberly Lu, and Dawn Song, · 2017
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“Introduction to convolutional neural networks,”
Jianxin Wu, · 2017
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“Speech commands: A dataset for limited-vocabulary speech recognition,”
Pete Warden, · 2018
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“Fine-pruning: Defending against backdooring attacks on deep neural networks,”
Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg, · 2018
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“Badnets: Evaluating backdooring attacks on deep neural networks,”
Tianyu Gu, Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg, · 2019
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“Strip: A defence against trojan attacks on deep neural networks,”
Yansong Gao, Change Xu, Derui Wang, Shiping Chen, Damith C Ranasinghe, and Surya Nepal, · 2019
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“nuscenes: A multimodal dataset for autonomous driving,”
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom, · 2020
Cited alongside, same era.
“A survey of autonomous driving: Common practices and emerging technologies,”
Ekim Yurtsever, Jacob Lambert, Alexander Carballo, and Kazuya Takeda, · 2020
Cited alongside, same era.
“Input-aware dynamic backdoor attack,”
Tuan Anh Nguyen and Anh Tran, · 2020
Cited alongside, same era.
“Adversarial example detection by classification for deep speech recognition,”
Saeid Samizade, Zheng-Hua Tan, Chao Shen, and Xiaohong Guan, · 2020
Cited alongside, same era.
“Automatic speech recognition: a survey,”
Mishaim Malik, Muhammad Kamran Malik, Khawar Mehmood, and Imran Makhdoom, · 2021
Cited alongside, same era.
“Adversarial neuron pruning purifies backdoored deep models,”
Dongxian Wu and Yisen Wang, · 2021
“Bppattack: Stealthy and efficient trojan attacks against deep neural networks via image quantization and contrastive adversarial learning,”
Zhenting Wang, Juan Zhai, and Shiqing Ma, · 2022
Later among the works it cites.
“Can you hear it? backdoor attacks via ultrasonic triggers,”
Stefanos Koffas, Jing Xu, Mauro Conti, and Stjepan Picek, · 2022
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“Opportunistic backdoor attacks: Exploring human-imperceptible vulnerabilities on speech recognition systems,”
Qiang Liu, Tongqing Zhou, Zhiping Cai, and Yonghao Tang, · 2022
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Avi Gazneli, Gadi Zimerman, Tal Ridnik, Gilad Sharir, and Asaf Noy, · 2022
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“Backdoor attacks against voice recognition systems: A survey,”
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Cited alongside, same era.
“Anti-backdoor learning: Training clean models on poisoned data,”
Yige Li, Xixiang Lyu, Nodens Koren, Lingjuan Lyu, Bo Li, and Xingjun Ma, · 2021
Cited alongside, same era.
“Wanet–imperceptible warping-based backdoor attack,”
Anh Nguyen and Anh Tran, · 2021
Cited alongside, same era.
“Keyword transformer: A self-attention model for keyword spotting,”
Axel Berg, Mark O’Connor, and Miguel Tairum Cruz, · 2021
Cited alongside, same era.
“Backdoor defense via decoupling the training process,”
Kunzhe Huang, Yiming Li, Baoyuan Wu, Zhan Qin, and Kui Ren, · 2022
Cited alongside, same era.
“The” beatrix”resurrections: Robust backdoor detection via gram matrices,”
Wanlun Ma, Derui Wang, Ruoxi Sun, Minhui Xue, Sheng Wen, and Yang Xiang, · 2022
Cited alongside, same era.
“Penalizing gradient norm for efficiently improving generalization in deep learning,”
Yang Zhao, Hao Zhang, and Xiuyuan Hu, · 2022
Cited alongside, same era.
Baochen Yan, Jiahe Lan, and Zheng Yan, · 2023
Later among the works it cites.
“Reconstructive neuron pruning for backdoor defense,”
Yige Li, Xixiang Lyu, Xingjun Ma, Nodens Koren, Lingjuan Lyu, Bo Li, and Yu-Gang Jiang, · 2023
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“Defenses in adversarial machine learning: A survey,”
Baoyuan Wu, Shaokui Wei, Mingli Zhu, Meixi Zheng, Zihao Zhu, Mingda Zhang, Hongrui Chen, Danni Yuan, Li Liu, and Qingshan Liu, · 2023
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“Going in style: Audio backdoors through stylistic transformations,”
Stefanos Koffas, Luca Pajola, Stjepan Picek, and Mauro Conti, · 2023
Later among the works it cites.
“Attacks in adversarial machine learning: A systematic survey from the life-cycle perspective,”
Baoyuan Wu, Zihao Zhu, Li Liu, Qingshan Liu, Zhaofeng He, and Siwei Lyu, · 2023
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“Magnitude-based neuron pruning for backdoor defens,”
Nan Li, Haoyu Jiang, and Ping Yi, · 2024
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“Towards stealthy backdoor attacks against speech recognition via elements of sound,”
Hanbo Cai, Pengcheng Zhang, Hai Dong, Yan Xiao, Stefanos Koffas, and Yiming Li, · 2024
Later among the works it cites.
“Flowmur: A stealthy and practical audio backdoor attack with limited knowledge,”
J. Lan, J. Wang, B. Yan, Z. Yan, and E. Bertino, · 2024
Later among the works it cites.