对抗样本防御技术在深度神经网络中的应用研究

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中图分类号：TP181 文献标志码：A 文章编号：2095-2945（2025）27-0185-04

Abstract：Withtherapiddevelopmentofdeeplearning technology，deepneuralnetworkshavemade breakthroughsinfields suchasimagerecognitionandnaturallanguageprocesing.However，theexistenceofadversarialsamplesseriouslythreatensthe securityandreliabilityofdepneuralnetworks.Thepurposeofthisstudyistosystematicallyexploretheapplicationof adversarialsampledefensetechnologyindeepneuralnetworks.Byanalyzingthecharacterisicsofthecountermeasuressamples andtheirthreats，weconductin-depthresearchontheprinciplesandmethodsofvariousdefensetechnologies，providing theoretical basis and practical guidance for building a saferand morereliable deep neural network system.

Keywords：adversarial samples;deep neural networks;defense technology；confrontation training;robustness

近年来，深度神经网络在计算机视觉、自然语言处理、语音识别等领域取得了突破性进展。（剩余4373字）