Journal of Computer Applications ›› 2020, Vol. 40 ›› Issue (6): 1680-1684.DOI: 10.11772/j.issn.1001-9081.2019111948

• Cyber security • Previous Articles     Next Articles

Wireless sensor network intrusion detection system based on sequence model

CHENG Xiaohui1,2, NIU Tong1, WANG Yanjun1   

  1. 1. College of Information Science and Engineering, Guilin University of Technology, Guilin Guangxi 541006, China
    2. Guangxi Key Laboratory of Embedded Technology and Intelligent System (Guilin University of Technology), Guilin Guangxi 541006, China
  • Received:2019-11-15 Revised:2020-01-03 Online:2020-06-10 Published:2020-06-18
  • Contact: WANG Yanjun, born in 1983, M. S., lecturer. Her research interests include Internet of things, embedded systems.
  • About author:CHENG Xiaohui, born in 1961, professor. His research interests include embedded systems, Internet of things.NIU Tong, born in 1996, M. S. candidate. His research interests include Internet of things, information security, artificial intelligence.WANG Yanjun, born in 1983, M. S., lecturer. Her research interests include Internet of things, embedded systems.
  • Supported by:
    National Natural Science Foundation of China (61662017, 61262075, 61862019), the Guangxi Natural Science Foundation (2017GXNSFAA198223), the Guangxi Young and Middle-aged Teachers’ Basic Ability Improvement Project(2017KY0256, 2018KY0248, 2019KY0285).

基于序列模型的无线传感网入侵检测系统

程小辉1,2, 牛童1, 汪彦君1   

  1. 1.桂林理工大学 信息科学与工程学院,广西 桂林 541006
    2.广西嵌入式技术与智能系统重点实验室 (桂林理工大学),广西 桂林 541006
  • 通讯作者: 汪彦君(1983—)
  • 作者简介:程小辉(1961—),男,江西樟树人,教授,博士生导师,主要研究方向:嵌入式系统、物联网.牛童(1996—),男,北京人,硕士研究生,主要研究方向:物联网、信息安全、人工智能.汪彦君(1983—),女,广西桂林人,讲师,硕士,主要研究方向:物联网、嵌入式系统。
  • 基金资助:
    国家自然科学基金资助项目(61662017,61262075,61862019);广西自然科学基金资助项目(2017GXNSFAA198223);广西中青年教师基础能力提升项目(2017KY0256,2018KY0248,2019KY0285)。

Abstract: With the rapid development of Internet of Things (IoT), more and more IoT node devices are deployed, but the accompanying security problem cannot be ignored. Node devices at the network layer of IoT mainly communicate through wireless sensor networks. Compared with the Internet, they are more open and more vulnerable to network attacks such as denial of service. Aiming at the network layer security problem faced by wireless sensor networks, a network intrusion detection system based on sequence model was proposed to detect and alarm the network layer intrusion, which achieved higher recognition rate and lower false positive rate. Besides, aiming at the security problem of the node host device faced by wireless sensor network node devices, with the consideration of the node overhead, a host intrusion detection system based on simple sequence model was proposed. The experimental results show that, the two intrusion detection systems for the network layer and the host layer of wireless sensor network both have the accuracy more than 99%, and the false detection rate about 1%, which meet the industrial requirements. These two proposed systems can comprehensively and effectively protect the wireless sensor network security.

Key words: intrusion detection system, deep learning, sequence model, Internet of Things (IoT) security, wireless sensor network security

摘要: 随着物联网(IoT)的快速发展,越来越多的IoT节点设备被部署,但伴随而来的安全问题也不可忽视。IoT的网络层节点设备主要通过无线传感网进行通信,其相较于互联网更开放也更容易受到拒绝服务等网络攻击。针对无线传感网面临的网络层安全问题,提出了一种基于序列模型的网络入侵检测系统,对网络层入侵进行检测和报警,具有较高的识别率以及较低的误报率。另外,针对无线传感网节点设备面临的节点主机设备的安全问题,在考虑节点开销的基础上,提出了一种基于简单序列模型的主机入侵检测系统。实验结果表明,针对无线传感网的网络层以及主机层的两个入侵检测系统的准确率都达到了99%以上,误报率在1%左右,达到了工业需求,这两个系统可以全面有效地保护无线传感网安全。

关键词: 入侵检测系统, 深度学习, 序列模型, 物联网安全, 无线传感网安全

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