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Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I

Research Article

Network APT Attack Detection Based on Big Data Analysis

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  • @INPROCEEDINGS{10.1007/978-3-030-51100-5_30,
        author={Guo-gen Fan and Jian-li Zhai},
        title={Network APT Attack Detection Based on Big Data Analysis},
        proceedings={Multimedia Technology and Enhanced Learning. Second EAI International Conference, ICMTEL 2020, Leicester, UK, April 10-11, 2020, Proceedings, Part I},
        proceedings_a={ICMTEL},
        year={2020},
        month={7},
        keywords={Big data analysis Network APT Attack detection Sensing network},
        doi={10.1007/978-3-030-51100-5_30}
    }
    
  • Guo-gen Fan
    Jian-li Zhai
    Year: 2020
    Network APT Attack Detection Based on Big Data Analysis
    ICMTEL
    Springer
    DOI: 10.1007/978-3-030-51100-5_30
Guo-gen Fan1,*, Jian-li Zhai2
  • 1: Guangzhou Huali Science and Technology Vocational College, Guangzhou
  • 2: Huali College Guangdong University of Technology, Guangzhou
*Contact email: fanguogen@foxmail.com

Abstract

In order to improve the security of the distributed optical fiber sensing network, the self-adaptive detection of the fiber sensing network needs to be carried out, and an overlap detection algorithm under the APT attack of the distributed optical fiber sensing network based on the spectral characteristic component and the big data analysis is proposed. the large data sampling model of the network APT attack is constructed, the attack characteristics and the related properties of the distributed optical fiber sensing network virus are simulated by adopting the spectrum correlation characteristic detection and the large-data quantization characteristic coding, and the large-data fusion and feature extraction of the APT attack information are realized, the output abnormal characteristic detection of the distributed optical fiber sensing network is carried out through the feature extraction result, a distributed optical fiber sensing network intrusion large data statistical analysis model is constructed, and a narrow-band signal spectrum offset correction method is adopted, And calculating the connection probability density and the individual infection probability of the APT attack node, and improving the detection capability of the network APT attack. The simulation results show that the algorithm can effectively implement the network APT attack detection, improve the security detection capability of the network APT attack, and has a good network security protection capability.

Keywords
Big data analysis Network APT Attack detection Sensing network
Published
2020-07-19
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-51100-5_30
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