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An Efficient Impersonation Attack Detection Method in Fog Computing 被引量:3

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摘要 Fog computing paradigm extends computing,communication,storage,and network resources to the network’s edge.As the fog layer is located between cloud and end-users,it can provide more convenience and timely services to end-users.However,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the network.The attacker acts as an impersonator to impersonate other legitimate users.Therefore,in this work,we present a detection technique to secure the FC environment.First,we model a physical layer key generation based on wireless channel characteristics.To generate the secret keys between the legitimate users and avoid impersonators,we then consider a Double Sarsa technique to identify the impersonators at the receiver end.We compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and Q-learning.The simulation results demonstrate that the method based on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate(FAR),miss detection rate(MDR),and average error rate(AER).
出处 《Computers, Materials & Continua》 SCIE EI 2021年第7期267-281,共15页 计算机、材料和连续体(英文)
基金 supported by Natural Science Foundation of China(61801008) The China National Key R&D Program(No.2018YFB0803600) Scientific Research Common Program of Beijing Municipal Commission of Education(No.KM201910005025) Chinese Postdoctoral Science Foundation(No.2020M670074).
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