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Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I

Research Article

Research on Clustering Algorithm of Heterogeneous Network Privacy Big Data Set Based on Cloud Computing

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  • @INPROCEEDINGS{10.1007/978-3-030-67871-5_33,
        author={Ming-hao Ding},
        title={Research on Clustering Algorithm of Heterogeneous Network Privacy Big Data Set Based on Cloud Computing},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2021},
        month={2},
        keywords={Cloud computing Heterogeneous network Big data set Clustering algorithm Similarity},
        doi={10.1007/978-3-030-67871-5_33}
    }
    
  • Ming-hao Ding
    Year: 2021
    Research on Clustering Algorithm of Heterogeneous Network Privacy Big Data Set Based on Cloud Computing
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-67871-5_33
Ming-hao Ding1,*
  • 1: Department of Computer and Software Technology, Tianjin Electronic Information College
*Contact email: dingrui8562@126.com

Abstract

With the rapid development and application of global information technology, big data era has come. China’s information security strategy needs to consider the complexity and timeliness of large-scale and heterogeneous network security behavior in big data’s time. In order to solve the problem of inaccurate and randomness of single clustering algorithm, a clustering algorithm based on cloud computing for heterogeneous network privacy big data set was proposed. The algorithm utilized the advantages of cloud computing to collect and extract features of big data sets. Then the similarity method was used to carry out the mining process of big data sets, so as to realize the clustering calculation process of big data sets. The algorithm was verified on the UCI dataset. The results showed that the efficiency and accuracy of the cloud computing-based big dataset clustering algorithm were better than the existing ones, indicating that the algorithm design and update strategy were effective.

Keywords
Cloud computing Heterogeneous network Big data set Clustering algorithm Similarity
Published
2021-02-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67871-5_33
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