Freeze-and-mutate: abnormal sample identification for DL applications through model core analysis

Author:

Wang Huiyan,Chen Ziqi,Xu Chang

Funder

Natural Science Foundation of Jiangsu Province

National Science Foundation of Jiangsu Province

Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Software

Reference70 articles.

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3. Bulusu, S., Kailkhura, B., Li, B., Varshney, P., Song, D.: Anomalous instance detection in deep learning: A survey. Technical report, Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), (2020)

4. Carlini, N., Wagner, D.: Adversarial examples are not easily detected: Bypassing ten detection methods. In: Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, pages 3–14, (2017)

5. Carlini, N., Wagner, D.: Towards evaluating the robustness of neural networks. In: Proceedings of the 38th IEEE Symposium on Security and Privacy (SP 2017), pages 39–57. IEEE, (2017)

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