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A Cross-Platform Instant Messaging User Association Method Based on Supervised Learning

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Big Data and Security (ICBDS 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1796))

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Abstract

To solve the multi-platform user association problem of complex trajectory matching process and high time cost in cross-platform association positioning of instant messaging users, and at the same time make full use of the information in user trajectories, this paper proposes a supervised learning-based cross-platform instant messaging user association positioning method. The algorithm firstly places probes in the area where the target may appear to obtain user information; then gets user trajectories through the obtained user distance information and time information; selects user features through the classification algorithm of supervised learning, and designs a cross-platform instant messaging user association localization method based on supervised learning, so as to increase the association efficiency and accuracy of cross-platform instant messaging user association. The method conducts specific experiments for the most commonly used instant messaging tools in China, WeChat and Stranger users, and the results show that the method can achieve efficient and reliable association for these two types of instant messaging users.

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Notes

  1. 1.

    NoxPlayer: https://www.yeshen.com.

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Funding

This work was supported by the National Natural Science Foundation of China (No. U1804263, 61872448, 62172435, and 62002386) and the Zhongyuan Science and Technology Innovation Leading Talent Project (No. 214200510019).

Author information

Authors and Affiliations

  1. School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, 450000, China

    Pei Zhou & Jiashan Guo

  2. State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, 450000, China

    Xiangyang Luo, Shaoyong Du & Wenqi Shi

Authors
  1. Pei Zhou
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  2. Xiangyang Luo
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  3. Shaoyong Du
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  4. Wenqi Shi
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  5. Jiashan Guo
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Corresponding author

Correspondence to Xiangyang Luo .

Editor information

Editors and Affiliations

  1. Nanjing Institute of Technology, Nanjing, China

    Yuan Tian

  2. Nanjing University of Information Science and Technology, Nanjing, Jiangsu, China

    Tinghuai Ma

  3. Chinese Academy of Sciences, Shenzhen, China

    Qingshan Jiang

  4. Nanjing University of Information Science and Technology, Nanjing, China

    Qi Liu

  5. King Saud University, Riyadh, Saudi Arabia

    Muhammad Khurram Khan

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The authors declare that they have no conflicts of interest to report regarding the present study.

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Zhou, P., Luo, X., Du, S., Shi, W., Guo, J. (2023). A Cross-Platform Instant Messaging User Association Method Based on Supervised Learning. In: Tian, Y., Ma, T., Jiang, Q., Liu, Q., Khan, M.K. (eds) Big Data and Security. ICBDS 2022. Communications in Computer and Information Science, vol 1796. Springer, Singapore. https://doi.org/10.1007/978-981-99-3300-6_6

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  • DOI: https://doi.org/10.1007/978-981-99-3300-6_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-3299-3

  • Online ISBN: 978-981-99-3300-6

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