Understand
Deep neural networks have achieved state-of-the-art performance on various tasks.
- However, lack of interpretability and transparency makes it easier for malicious attackers to inject trojan backdoor into the neural networks, which will make the model behave abnormally when a backdoor sample with a specific trigger is input.
- In this paper, we propose NeuronInspect, a framework to detect trojan backdoors in deep neural networks via output explanation techniques.
- NeuronInspect first identifies the existence of backdoor attack targets by generating the explanation heatmap of the output layer.
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Similar
Neural cleanse: Identifying and mitigating backdoor attacks in neural networks
Wang, B.; Yao, Y.; Shan, S.; Li, H.; Viswanath, B.; Zheng, H.; and Zhao, B. Y
Cited in the paper.
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