面向僵尸网络DGA攻击的智能检测技术与对抗策略研究

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中图分类号：TP393 文献标志码：A 文章编号：0253-2395（2025）04-0725-16

Abstract：Botnets candynamicallgenerate numerous unpredictabledomainsviaDomain GenerationAlgorithms （DGA）toelude traditionalstaticdetectio，ehancingthestealthndpersistenceofaliciosactivitis.AsDAtechnologyadvancs，tradtioale tectionmethodsarefacinggrowingchalenges.Eficientlyidentifyinganddefendingagainstthesedomainshasbecomecrucialincy bersecurity.This papercomprehensivelyanalyzes mainstreamDGAdetection technologies，includingthose basedonstatisticalfeatures，machineleaing，nddeepleaing.Itdelvesintotheirpinciples，applicationscenarios，ndperformanceucovingliita tions nfalsepositivetes，omputatioalomplexityatasesie，anddptabilitytoeGAs.Finalytepperproo vativedirectionsfordplearnng-baseddetectionandcrossdomaincollaborativedetection.Combinedwithtraffcbehavioranaly sis andgeneratio-patenblckingmecansms，webuildamulti-ayered，ntegatedDGAdeensestem，oferingideasto improve detection effectiveness，accuracy，and adaptability.

Key words： botnet; domain generation algorithm; domain detection; machine learning

0 引言

O.1研究背景与问题

随着互联网技术的快速发展和恶意软件攻击方式的持续升级，僵尸网络（Botnet）已经构成全球网络安全领域中的一个重大隐患。（剩余31730字）