Adversarial attacks and defenses in deep learning

Autor:	LIU Ximeng, XIE Lehui, WANG Yaopeng, LI Xuru
Jazyk:	English<br />Chinese
Rok vydání:	2020
Předmět:	adversarial examples adversarial attacks adversarial defenses deep learning security Electronic computers. Computer science QA75.5-76.95
Zdroj:	网络与信息安全学报, Vol 6, Iss 5, Pp 36-53 (2020)
Druh dokumentu:	article
ISSN:	2096-109x 2096-109X
DOI:	10.11959/j.issn.2096-109x.2020071
Popis:	The adversarial example is a modified image that is added imperceptible perturbations, which can make deep neural networks decide wrongly. The adversarial examples seriously threaten the availability of the system and bring great security risks to the system. Therefore, the representative adversarial attack methods were analyzed, including white-box attacks and black-box attacks. According to the development status of adversarial attacks and defenses, the relevant domestic and foreign defense strategies in recent years were described, including pre-processing, improving model robustness, malicious detection. Finally, future research directions in the field of adversarial attacks and adversarial defenses were given.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/698d22d5f8bd4c52a952992c06ba3e4d Zobrazit plný text záznamu View record in DOAJ