ARTICLE
Volume 10,Issue 7
27 February 2026
A Survey on Artificial Intelligence Systems Robustness: Adversarial Attacks and Defenses
Wei Zheng
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1
Sichuan Forestry and Grassland Administration, Chengdu 610081, China,
JERA 2026 , 10(1), 182–191;
https://doi.org/10.26689/jera.v10i1.13989
© 2026 by the Authors. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract
Artificial intelligence systems have achieved widespread applications across many fields such as image classification, speech recognition, and game playing. However, as their decision-making logic is primarily learned from data, their outputs are highly sensitive to data anomalies and are particularly vulnerable to adversarial perturbations. This paper conducts a comprehensive survey on the robustness of artificial intelligence systems, reviewing classical adversarial attack and defense methods, and summarizing future development trends. We hope this work can provide valuable insights for research on the robustness of artificial intelligence systems and support the development of trustworthy artificial intelligence.
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