计算机工程与应用2026，Vol.62Issue(2)：54-72,19.DOI:10.3778/j.issn.1002-8331.2504-0053
脉冲神经网络对抗样本攻击与防御综述
Survey of Adversarial Example Attack and Defense of Spiking Neural Networks
摘要
Abstract
With the wide deployment and application of spiking neural networks,their security problems have become more and more obvious,especially the threat from adversarial example attacks.Therefore,the adversarial example attack methods and defense measures in spiking neural networks are investigated.Firstly,the adversarial sample attack methods are studied,and the software layer is sorted out from the gradient attack,migration learning attack,encoding perturbation attack and sensor attack.The hardware layer deals with power injection attack,side channel attack and Trojan horse attack.Secondly,the defense measures of adversarial samples are studied.The defense measures of the software layer are sorted from adversarial training,input filtering,improved coding,feature network analysis and model fusion.The defense mea-sures of hardware layer are discussed from two parts of circuit optimization and security framework.Then,the application of adversarial examples in model security research and CAPTCHA anti-identification is discussed.Finally,the current challenges and future prospects are put forward and the whole paper is summarized.关键词
脉冲神经网络(SNN)/对抗样本攻击/对抗样本防御/人工智能模型安全Key words
spiking neural network(SNN)/adversarial example attack/adversarial example defense/artificial intelli-gence model security分类
信息技术与安全科学引用本文复制引用
王晓璐,岳鹏飞,张家琪,姬婕,董航,孔德懿..脉冲神经网络对抗样本攻击与防御综述[J].计算机工程与应用,2026,62(2):54-72,19.基金项目
内蒙古自然科学基金(2023QN06008) （2023QN06008）
内蒙古自治区科技厅项目(2024150001000215) （2024150001000215）
校级科研启动金(DC2200001311) （DC2200001311）
内蒙古自治区直属高校基本科研业务费项目(ZTY2024063,ZTY2025036). （ZTY2024063,ZTY2025036）
