Electromagnetic radiation based continuous authentication in edge computing enabled internet of things

被引:13
|
作者
Wang, Jun [1 ]
Ni, Mingtao [2 ,5 ]
Wu, Fusheng [3 ]
Liu, Shubo [4 ]
Qin, Jun [1 ]
Zhu, Rongbo [1 ]
机构
[1] South Cent Univ Nationalities, Coll Comp Sci, Wuhan 430074, Hubei, Peoples R China
[2] Wuhan Univ, Sch Cyber Sci & Engn, Wuhan 430074, Hubei, Peoples R China
[3] Guizhou Univ Finance & Econ, Guizhou Key Lab Econ Syst Simulat, Guiyang 550025, Guizhou, Peoples R China
[4] Wuhan Univ, Sch Comp, Wuhan 430074, Hubei, Peoples R China
[5] Leshan Normal Univ, Sch Comp Sci, Leshan 614000, Peoples R China
基金
中国国家自然科学基金;
关键词
Electromagnetic radiation; Continuous authentication; Internet of things; Edge computing; CONTINUOUS USER AUTHENTICATION; BIG DATA; SECURITY; CLOUD; PRIVACY;
D O I
10.1016/j.sysarc.2018.12.003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
With the rapid proliferation of Internet of Things, the centralized cloud faces the performance problems caused by remote network access and real-time services. To ensure good performance, edge computing paradigm emerges, and requires a secure authentication between edge host and cloud server to safeguard resources against any illegitimate access. Securing edge host authentication is an effective method and cornerstone to protect the information security in edge computing. Existing methods most recognize an entity's identity by password only once at the time of initial stage, which may lead to security problem. Continuous authentication as a novel authentication modality has the ability to alleviate this issue. Unlike the authentication operating merely at point-of-entry, a continuous edge host authentication method is proposed on the basis of electromagnetic radiation which reflects the behavioral characteristics of edge host with heterogeneous hardware. We demonstrate the feasibility of the proposed method through analysis of success rate from ten thousand waterfall spectrograms, and experimental results show that the average success rate of 95% has been achieved by support vector machine combining multiple features.
引用
收藏
页码:53 / 61
页数:9
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