Research on adversarial attacks and defense

Yu Xie; Luqiao Zhang; Yi Xiang

doi:10.1117/12.2640997

2 December 2022 Research on adversarial attacks and defense

Yu Xie, Luqiao Zhang, Yi Xiang

Proceedings Volume 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022); 1228807 (2022) https://doi.org/10.1117/12.2640997
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 2022, Zhuhai, China

Abstract

Deep learning is widely used in our daily life to solve some complex and tedious problems. In practical applications, if it was exploited by attackers would affect the reliability and security of the deep learning model. This article mainly introduces some attacks methods of generating adversarial examples from Generative Adversarial Networks(GAN) in recent years and related algorithms that use adversarial training to improve the robustness of deep learning models. At the end of the article, drawing on the reviewed literature, we present a broader outlook of adversarial attacks research direction.

Citation Download Citation

Yu Xie, Luqiao Zhang, and Yi Xiang "Research on adversarial attacks and defense", Proc. SPIE 12288, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022), 1228807 (2 December 2022); https://doi.org/10.1117/12.2640997

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