计算机应用 ›› 2019, Vol. 39 ›› Issue (2): 464-469.DOI: 10.11772/j.issn.1001-9081.2018081955

• 网络空间安全 • 上一篇    下一篇

基于物联网设备指纹的情境认证方法

杜俊雄1,2, 陈伟1,2, 李雪妍1,2   

  1. 1. 南京邮电大学 计算机学院, 南京 210023;
    2. 江苏省大数据安全与智能处理重点实验室, 南京 210023
  • 收稿日期:2018-09-25 修回日期:2018-10-21 出版日期:2019-02-10 发布日期:2019-02-15
  • 通讯作者: 陈伟
  • 作者简介:杜俊雄(1993-),男,江苏苏州人,硕士研究生,主要研究方向:网络安全;陈伟(1979-),男,江苏淮安人,教授,博士,CCF会员,主要研究方向:网络安全;李雪妍(1993-),女,江苏南京人,硕士研究生,主要研究方向:网络安全。
  • 基金资助:
    国家自然科学基金资助项目(61602258)。

Contextual authentication method based on device fingerprint of Internet of Things

DU Junxiong1,2, CHEN Wei1,2, LI Xueyan1,2   

  1. 1. College of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing Jiangsu 210023, China;
    2. Jiangsu Key Laboratory of Big Data Security and Intelligent Processing, Nanjing Jiangsu 210023, China
  • Received:2018-09-25 Revised:2018-10-21 Online:2019-02-10 Published:2019-02-15
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61602258).

摘要: 针对物联网设备中因非法设备接入带来的远程控制安全问题,提出一种基于设备指纹的情境认证方法。首先,通过提出的对交互流量中单个字节的分析技术,提取物联网设备指纹;其次,提出认证的流程框架,根据设备指纹在内的六种情境因素进行身份认证,设备认证通过才可允许访问;最后,对物联网设备进行实验,提取相关设备指纹特征,结合决策树分类算法,从而验证情境认证方法的可行性。实验中所提方法的分类准确率达90%,另外10%误判率为特殊情况但也符合认证要求。实验结果表明基于物联网设备指纹的情境认证方法可以确保只有可信的物联网终端设备接入网络。

关键词: 物联网, 网络安全, 设备指纹, 情境认证, 远程控制

Abstract: Aiming at the security problem of remote control brought by illegal device access in Internet of Things (IoT), a contextual authentication method based on device fingerprint was proposed. Firstly, the fingerprint of IoT device was extracted by a proposed single byte analysis method in the interaction traffic. Secondly, the process framework of the authentication was proposed, and the identity authentication was performed according to six contextual factors including device fingerprint. Finally, in the experiments on IoT devices, relevant device fingerprint features were extracted and decision tree classification algorithms were combined to verify the feasibility of contextual authentication method. Experimental results show that the classification accuracy of the proposed method is 90%, and the 10% false negative situations are special cases but also meet the certification requirements. The results show that the contextual authentication method based on the fingerprint of IoT devices can ensure that only trusted IoT terminal equipment access the network.

Key words: Internet of Things (IoT), network security, device fingerprint, contextual authentication, remote control

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