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Security Analysis of Social Network Topic Mining Using Big Data and Optimized Deep Convolutional Neural Network.

Kunzhi Tang1, Chengang Zeng2, Yuxi Fu3

  • 1College of Engineering & Computer Science, The Australian National University, Canberra 2615, Australia.

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Summary

This study introduces a novel network security topic detection model using big data and deep learning. The model achieves high accuracy in identifying social network security issues, enhancing data protection.

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Data Science

Background:

  • Social network users' behavior can inadvertently expose private data.
  • Effective analysis of social network big data is crucial for identifying security threats.

Purpose of the Study:

  • To develop a network security topic detection model integrating Convolutional Neural Network (CNN) and social network big data.
  • To enhance the analysis and detection of social network security issues using advanced deep learning techniques.

Main Methods:

  • Utilized Deep Convolutional Neural Network (DCNN) for social network security issue analysis.
  • Employed Long Short-Term Memory (LSTM) algorithm for Weibo topic information extraction.
  • Combined DCNN and social network big data technology for topic mining and data analysis.

Main Results:

  • The developed model achieved a recognition accuracy of 96.17% after 120 iterations, outperforming other models by at least 5.4%.
  • The intrusion detection model demonstrated accuracy, recall, and F1 values of 88.57%, 75.22%, and 72.05%, respectively, exceeding other algorithms by at least 3.1%.
  • The improved DCNN model significantly reduced training (65.86s) and testing (27.90s) times, indicating lower latency in deep learning for network data security.

Conclusions:

  • The improved DCNN model offers superior performance for network data security transmission with reduced latency.
  • The model effectively addresses social network security challenges by accurately detecting relevant topics and intrusions.
  • This research highlights the potential of combining deep learning with big data analytics for robust cybersecurity solutions.