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Backdoor attacks pose a significant threat to neural networks, enabling adversaries to manipulate model outputs on specific inputs, often with devastating consequences, especially in critical applications.
Catastrophic interference in connectionist networks: The sequential learning problem
Neal J. Cohen Michael McCloskey · 1989
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, and Dhruv Batra · 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 Xiaodong Song · 2017
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Badnets: Identifying vulnerabilities in the machine learning model supply chain
Tianyu Gu, Brendan Dolan-Gavitt, and Siddharth Garg · 2017
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Learning without forgetting
Zhizhong Li and Hoiem Derek · 2017
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Universal adversarial perturbations
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Omar Fawzi, and Pascal Frossard · 2017
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Network Security
Synopsis: Open source security and risk analysis · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Detecting backdoor attacks on deep neural networks by activation clustering
Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Ben Edwards, Taesung Lee, Ian Molloy, and B. Srivastava · 2018
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Sentinet: Detecting localized universal attacks against deep learning systems
Edward Chou, Florian Tramèr, and Giancarlo Pellegrino · 2018
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Backdoor embedding in convolutional neural network models via invisible perturbation
Cong Liao, Haoti Zhong, Anna Cinzia Squicciarini, Sencun Zhu, and David J. Miller · 2018
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Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization
David J. Freedman Nicolas Y. Masse, Gregory D. Grant · 2018
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Clean-label backdoor attacks
Alexander Turner, Dimitris Tsipras, and Aleksander Madry · 2018
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Continual learning in neural networks
R Aljundi · 2019
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Invisible backdoor attacks on deep neural networks via steganography and regularization
Shaofeng Li, Minhui Xue, Benjamin Zi Hao Zhao, Haojin Zhu, and Xinpeng Zhang · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
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Defending neural backdoors via generative distribution modeling
Ximing Qiao, Yukun Yang, and Hai Helen Li · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
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Meta-transfer learning for few-shot learning
Qianru Sun, Yaoyao Liu, Tat-Seng Chua, and Bernt Schiele · 2019
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Can you really backdoor federated learning?
Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, and H. B. McMahan · 2019
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Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Bolun Wang, Yuanshun Yao, Shawn Shan, Huiying Li, Bimal Viswanath, Haitao Zheng, and Ben Y. Zhao · 2019
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Detecting ai trojans using meta neural analysis
Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, and Bo Li · 2019
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Latent backdoor attacks on deep neural networks
Lifelong robot learning
Erhan Oztop and Emre Ugur · 2021
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Adversarial targeted forgetting in regularization and generative based continual learning models
Muhammad Umer and Robi Polikar · 2021
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Dataset security for machine learning: Data poisoning, backdoor attacks, and defenses
Micah Goldblum, Liam Fowl, Chawin Sitawarin, Zifan He, Gavin Taylor, and Tom Goldstein · 2022
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Pareto optimality, economy–effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons
Peter Jedlicka, Alexander D. Bird, and Hermann Cuntz · 2022
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Targeted data poisoning attacks against continual learning neural networks
Huayu Li and Gregory Ditzler · 2022
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Yuanshun Yao, Huiying Li, Haitao Zheng, and Ben Y Zhao · 2019
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How to backdoor federated learning
Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, and Vitaly Shmatikov · 2020
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Noise-response analysis for rapid detection of backdoors in deep neural networks
N. Benjamin Erichson, Dane Taylor, Qixuan Wu, and Michael W. Mahoney · 2020
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Can adversarial weight perturbations inject neural backdoors
Siddhant Garg, Adarsh Kumar, Vibhor Goel, and Yingyu Liang · 2020
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Input-aware dynamic backdoor attack
A. Nguyen and A. Tran · 2020
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Hidden trigger backdoor attacks
Aniruddha Saha, Akshayvarun Subramanya, and Hamed Pirsiavash · 2020
Cited alongside, same era.
Targeted forgetting and false memory formation in continual learners through adversarial backdoor attacks
Muhammad Umer, Glenn Dawson, and Robi Polikar · 2020
Cited alongside, same era.
Huiying Li, Arjun Nitin Bhagoji, Yuxin Chen, Haitao Zheng, and Ben Y Zhao · 2022
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Learning universal adversarial perturbation by adversarial example
Maosen Li, Yanhua Yang, Kun Wei, Xu Yang, and Heng Huang · 2022
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Dynamic backdoor attacks against machine learning models
Ahmed Salem, Rui Wen, Michael Backes, Shiqing Ma, and Yang Zhang · 2022
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Three types of incremental learning
Gido M van de Ven, Tinne Tuytelaars, and Andreas S Tolias · 2022
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Adversarial unlearning of backdoors via implicit hypergradient
Yi Zeng, Si Chen, Won Park, Zhuoqing Morley Mao, Ming Jin, and R. Jia · 2022
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Access: Advancing innovation: Nsf’s advanced cyberinfrastructure coordination ecosystem: Services & support
Timothy J Boerner, Stephen Deems, Thomas R Furlani, Shelley L Knuth, and John Towns · 2023
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Adversarial clean label backdoor attacks and defenses on text classification systems
Ashim Gupta and Amrith Krishna · 2023
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Data poisoning attack aiming the vulnerability of continual learning
Gyojin Han, Jaehyun Choi, Hyeong Gwon Hong, and Junmo Kim · 2023
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Poisoning generative replay in continual learning to promote forgetting
Siteng Kang, Zhan Shi, and Xinhua Zhang · 2023
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Narcissus: A practical clean-label backdoor attack with limited information
Yi Zeng, Minzhou Pan, Hoang Anh Just, Lingjuan Lyu, Meikang Qiu, and Ruoxi Jia · 2023
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Efficient trigger word insertion
Yueqi Zeng, Ziqiang Li, Pengfei Xia, Lei Liu, and Bin Li · 2023
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Backdoor attacks against incremental learners: An empirical evaluation study
Yiqi Zhong, Xianming Liu, Deming Zhai, Junjun Jiang, and Xiangyang Ji · 2023
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State of AI report, 2023
Nathan Benaich and Ian Hogarth · 2024
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Nws: Natural textual backdoor attacks via word substitution
Wei Du, TongXin Yuan, Haodong Zhao, and Gongshen Liu · 2024
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Recent advances of foundation language models-based continual learning: A survey
Yutao Yang, Jie Zhou, Xuanwen Ding, Tianyu Huai, Shunyu Liu, Qin Chen, Yuan Xie, and Liang He · 2024
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