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基于机器学习的网络异常检测方法综述 被引量:15

Research on Network Anomaly Detection Method Basedon Machine Learning
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摘要 随着通信、大数据及云计算等技术的成熟应用和广泛普及,伴随着设备的急剧增多,数据爆炸式增长,使网络环境变得日益复杂,给网络安全带来巨大隐患。为此,针对网络安全技术发展需要,叙述了如何应用人工智能(AI:Artificial Intelligence)帮助解决网络安全问题。针对网络中的特定领域或网络技术,对如何应用机器学习(ML:Machine Learning)方法提升网络安全性能进行了详细分析。首先,总结了在使用AI打击网络攻击方面的现有研究工作,包括采用传统的机器学习方法和现有的深度学习解决方案。然后,分析了AI本身可能遭受的反击,剖析了它们的特点,并对相应的防御方法进行了分类。最后,提出了一些先进的人工智能网络安全技术的高级概念,并展望了未来人工智能如何更好地应用到网络安全领域。 In recent years,benefiting from the mature application of communication,big data,cloud computing and other technologies,“Internet+”has been widely popularized in people’s livelihood,economy and government affairs.With the rapid increase of equipment and explosive growth of data,the network environment becomes increasingly complex and brings huge hidden dangers to network security.The need for the development of network security technology and how to apply artificial intelligence AI(Artificial Intelligence)to help solve some problems is introduced.And how to apply machine learning ML(Machine Learning)to improve network security performance is analyzed in detail for specific domain or specific network technology.First,we summarize existing research work on using AI to combat cyber attacks,including using traditional machine learning approaches and existing deep learning solutions.We then analyzed the counterattacks that the AI itself might be subjected to,dissected their characteristics,and classified the appropriate defenses.We also provide some advanced concepts of artificial intelligence network security technology i.e.how to better apply artificial intelligence to the field of network security in the future.
作者 张赛男 孙彪 ZHANG Sainan;SUN Biao(School of Journalism and Communication,Jilin University of Finance and Economics,Changchun 130022,China;Headquarters,Changchun Detachment of the Armed Police,Changchun 130051,China)
出处 《吉林大学学报(信息科学版)》 CAS 2021年第6期732-742,共11页 Journal of Jilin University(Information Science Edition)
基金 吉林省教育厅“十三五”社会科学科研基金资助项目(JJKH20200149SK) 吉林省教育科学规划基金资助项目(GH20232) 吉林省科技厅科技发展计划基金资助项目(20190601015FG)。
关键词 机器学习 网络安全 人工智能 防御技术 machine learning network security artificial intelligence defense technology
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