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ReLFA:Resist Link Flooding Attacks via Renyi Entropy and Deep Reinforcement Learning in SDN-IoT

查看全文 作　　者：Jiushuang [1]Wang;Ying [1,2]Liu;Weiting [1]Zhang;Xincheng [2,3]Yan;Na [2,3]Zhou;Zhihong [2,3]Jiang 高影响力作者 机构地区：[1]School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China;[2]State Key Laboratory of Mobile Network and Mobile Multimedia Technology,Shenzhen 518055,China;[3]ZTE Corporation,Nanjing 210012,China高影响力机构 出　　处：《China Communications》索引2022年第19卷第7期,共15页高影响力期刊 基　　金：supported by the Fundamental Research Funds under Grant 2021JBZD204;ZTE industry-university research cooperation fund project “Research on network identity trusted communication technology architecture”;State Key Laboratory of Mobile Network and Mobile Multimedia Technology 摘　　要：Link flooding attack(LFA)is a fresh distributed denial of service attack(DDoS).Attackers can cut off the critical links,making the services in the target area unavailable.LFA manipulates legal lowspeed flow to flood critical links,so traditional technologies are difficult to resist such attack.Meanwhile,LFA is also one of the most important threats to Internet of things(IoT)devices.The introduction of software defined network(SDN)effectively solves the security problem of the IoT.Aiming at the LFA in the software defined Internet of things(SDN-IoT),this paper proposes a new LFA mitigation scheme ReLFA.Renyi entropy is to locate the congested link in the data plane in our scheme,and determines the target links according to the alarm threshold.When LFA is detected on the target links,the control plane uses the method based on deep reinforcement learning(DRL)to carry out traffic engineering.Simulation results show that ReLFA can effectively alleviate the impact of LFA in SDN IoT.In addition,the rerouting time of ReLFA is superior to other latest schemes. 关 键 词：link flooding attacks renyi entropy deep reinforcement learning
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