Backdoor Attacks to Deep Neural Networks: A Survey of the Literature, Challenges, and Future Research Directions

Backdoor Attacks to Deep Neural Networks: A Survey of the Literature, Challenges, and Future Research Directions

Deep neural network (DNN) classifiers are potent instruments that can be used in various security-sensitive applications. Nonetheless, they are vulnerable to certain attacks that impede or distort their learning process. For example, backdoor attacks involve polluting the DNN learning set with a few...

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Bibliographic Details
Main Authors: Orson Mengara, Anderson Avila, Tiago H. Falk
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Backdoor attack
deep learning
vulnerability detection
trojan attack
neural trojan
Online Access:https://ieeexplore.ieee.org/document/10403914/

Internet

https://ieeexplore.ieee.org/document/10403914/

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