基于AI的汽車智能網(wǎng)聯(lián)系統(tǒng)信息安全檢測技術(shù)

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中圖分類號：U463.6 文獻標(biāo)識碼：A 章編號：1003-8639（2025）08-0062-03

【Abstract】With the wideapplicationof intellgentconnected vehicles，the securityof on-board informationsystems isfacingchallnges.Inviewofthelimitationsofexistingdetectiontechnologies，thisarticleconstructsanAl-based securitydetection framework through multi-dimensional featurefusionandoptimizationof deep learning models.This framework covers keytechnologiessuchasabnormalnetworktraficdetection，intrusionbehavioridentificationandscurity risk assessment.Tests show that thecomprehensive accuracyrate of the ResNet-BiLSTM hybrid model reaches 98.7% ， and thereasoningdelaymets theon-boardrequirements.It efectively enhances the information protectioncapabilityof theautomotive intellgent connected vehicle system and provides technical support forthe safetyof intelligentvehicles.

【Key words】 intelligent connected vehicles；security detection；deep learning

0 引言

隨著智能網(wǎng)聯(lián)汽車的廣泛應(yīng)用，車載信息系統(tǒng)面臨網(wǎng)絡(luò)攻擊、數(shù)據(jù)泄露及惡意入侵等安全挑戰(zhàn)，這些威脅嚴(yán)重危及行車安全與用戶隱私。（剩余4074字）