International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Real Time Arabic Communities Attack Detection on Online Social Networks

  • Jalal S Alowibdi (Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah)
  • Received : 2024.08.05
  • Published : 2024.08.30
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Abstract

The dynamic nature of Online Social Networks (OSNs), especially on platforms like Twitter, presents challenges in identifying and responding to community attacks, particularly within Arabic content. The proposed integrated system addresses these challenges by achieving 91% accuracy in detecting real-time community event attacks while efficiently managing computational costs. This is accomplished through the use of specialized integrated approach clustering to detect both major and minor attacks. Additionally, the system leverages clustering algorithms, temporal modules, and social network graphs to identify events, map communities, and analyze online dynamics. An extensive parameter sensitivity analysis was conducted to fine-tune the algorithm, and the system's effectiveness was validated using a benchmark dataset, demonstrating substantial improvements in event detection.

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References

  1. Alowibdi, Jalal S., Ugo A. Buy, and Philip Yu. "Language independent gender classification on Twitter." Proceedings of the 2013 IEEE/ACM international conference on advances in social networks analysis and mining. 2013.
  2. Khan, H. U., Daud, A., Ishfaq, U., Amjad, T., Aljohani, N., Abbasi, R. A., & Alowibdi, J. S. (2017). Modelling to identify influential bloggers in the blogosphere: A survey. Computers in Human Behavior, 68, 64-82.
  3. Alowibdi, J. S., Buy, U. A., & Yu, P. (2013, December). Empirical evaluation of profile characteristics for gender classification on twitter. In 2013 12th international conference on machine learning and applications (Vol. 1, pp. 365-369). IEEE.
  4. Saving lives using social media: analysis of the role of twitter for personal blood donation requests and dissemination.
  5. Abbasi, R. A., Maqbool, O., Mushtaq, M., Aljohani, N. R., Daud, A., Alowibdi, J. S., & Shahzad, B. (2018). Saving lives using social media: analysis of the role of twitter for personal blood donation requests and dissemination. Telematics and Informatics, 35(4), 892-912.
  6. Alowibdi, J. S., Buy, U. A., Philip, S. Y., & Stenneth, L. (2014, August). Detecting deception in online social networks. In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) (pp. 383-390). IEEE.
  7. Alowibdi, J. S., Buy, U. A., Yu, P. S., Ghani, S., & Mokbel, M. (2015). Deception detection in Twitter. Social network analysis and mining, 5, 1-16.
  8. Jarwar, M. A., Abbasi, R. A., Mushtaq, M., Maqbool, O., Aljohani, N. R., Daud, A., ... & Chong, I. (2017). CommuniMents: A framework for detecting community based sentiments for events. International Journal on Semantic Web and Information Systems (IJSWIS), 13(2), 87-108.
  9. Alowibdi, J. S., Alshdadi, A. A., Daud, A., Dessouky, M. M., & Alhazmi, E. A. (2021). Coronavirus pandemic (COVID-19): Emotional toll analysis on Twitter. International Journal on Semantic Web and Information Systems (IJSWIS), 17(2), 1-21.
  10. Gillani, M., Ilyas, M. U., Saleh, S., Alowibdi, J. S., Aljohani, N., & Alotaibi, F. S. (2017, April). Post summarization of microblogs of sporting events. In Proceedings of the 26th international conference on World Wide Web companion (pp. 59-68).
  11. Sakaki, Takeshi, Makoto Okazaki, and Yutaka Matsuo. "Earthquake shakes twitter users: real-time event detection by social sensors." Proceedings of the 19th international conference on World wide web. 2010.
  12. Petrovic, Sasa, Miles Osborne, and Victor Lavrenko. "Streaming first story detection with application to twitter." Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT'10).
  13. Cordeiro, M. Twitter event detection: combining wavelet analysis and topic inference summarization. In Doctoral symposium on informatics engineering (Vol. 1, pp. 11-16).
  14. Alharbi, A., & Lee, M. (2021, April). Kawarith: an Arabic Twitter corpus for crisis events. In Proceedings of the Sixth Arabic Natural Language Processing Workshop (pp. 42-52).
  15. Alsaedi, Nasser, and Pete Burnap. "Arabic event detection in social media." Computational Linguistics and Intelligent Text Processing: 16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings, Part I 16. Springer International Publishing, 2015.
  16. Alkouz, Balsam, and Zaher Al Aghbari. "Fusion of Multiple Arabic Social Media Streams for Traffic Events Detection." 2022 7th International Conference on Big Data Analytics (ICBDA). IEEE, 2022.