Cluster Computing

, Volume 22, Supplement 4, pp 9889–9904 | Cite as

Mobile network intrusion detection for IoT system based on transfer learning algorithm

  • Lianbing Deng
  • Daming LiEmail author
  • Xiang Yao
  • David Cox
  • Haoxiang Wang


The open deployment environment and limited resources of the Internet of things (IoT) make it vulnerable to malicious attacks, while the traditional intrusion detection system is difficult to meet the heterogeneous and distributed features of the Internet of things. The security and privacy protection of IoT is directly related to the practical application of IoT. In this paper, We analyze the characteristics of networking security and security problems, and discuss the system framework of Internet security and some key security technologies, including key management, authentication and access control, routing security, privacy protection, intrusion detection and fault tolerance and intrusion etc. This paper introduces the current problems of IoT in network security, and points out the necessity of intrusion detection. Several kinds of intrusion detection technologies are discussed, and its application on IoT architecture is analyzed. We compare the application of different intrusion detection technologies, and make a prospect of the next phase of research. Using data mining and machine learning methods to study network intrusion technology has become a hot issue. A single class feature or a detection model is very difficult to improve the detection rate of network intrusion detection. The performance of the proposed model is validated through the public databases.


Intrusion detection Internet of things Information security Pop learning 



This paper is supported by the The Project of Macau Foundation (No. M1617): The First-phase Construction of Big-Data on Smart Macao.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Lianbing Deng
    • 1
    • 2
  • Daming Li
    • 3
    • 4
    • 5
    Email author
  • Xiang Yao
    • 2
  • David Cox
    • 6
  • Haoxiang Wang
    • 7
    • 8
  1. 1.Huazhong University of Science and TechnologyWuhanChina
  2. 2.Zhuhai Da Hengqin Science and Technology Development Co., Ltd.HengqinChina
  3. 3.The Post-Doctoral Research Center of Zhuhai Da Hengqin Science and Technology Development Co., Ltd.HengqinChina
  4. 4.City University of MacauTaipaMacau
  5. 5.International Postdoctoral Science and Technology Research Institute Co., LtdWuhanChina
  6. 6.Harvard John A. Paulson School of Engineering & Applied SciencesHarvard UniversityCambridgeUSA
  7. 7.Cornell UniversityIthacaUSA
  8. 8.GoPerception LaboratoryNew YorkUSA

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