DLFuzz: differential fuzzing testing of deep learning systems

Author:

Guo Jianmin1,Jiang Yu1,Zhao Yue1,Chen Quan2,Sun Jiaguang1

Affiliation:

1. Tsinghua University, China

2. Shanghai Jiao Tong University, China

Publisher

ACM

Reference21 articles.

1. Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D Jackel Mathew Monfort Urs Muller Jiakai Zhang et al. 2016. End to end learning for self-driving cars. arXiv preprint arXiv:1604.07316 (2016). Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D Jackel Mathew Monfort Urs Muller Jiakai Zhang et al. 2016. End to end learning for self-driving cars. arXiv preprint arXiv:1604.07316 (2016).

2. Yuanliang Chen Yu Jiang Jie Liang Mingzhe Wang and Xun Jiao. 2018. EnFuzz: From Ensemble Learning to Ensemble Fuzzing. arXiv preprint arXiv:1807.00182 (2018). Yuanliang Chen Yu Jiang Jie Liang Mingzhe Wang and Xun Jiao. 2018. EnFuzz: From Ensemble Learning to Ensemble Fuzzing. arXiv preprint arXiv:1807.00182 (2018).

3. ImageNet: A large-scale hierarchical image database

4. Shixiang Gu and Luca Rigazio. 2014. Towards deep neural network architectures robust to adversarial examples. arXiv preprint arXiv:1412.5068 (2014). Shixiang Gu and Luca Rigazio. 2014. Towards deep neural network architectures robust to adversarial examples. arXiv preprint arXiv:1412.5068 (2014).

5. Deep Residual Learning for Image Recognition

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