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A Novel Machine Learning Algorithm for Spammer Identification in Industrial Mobile Cloud Computing
Authors
12Department of Computer Science and Engineering, IES College of Engineering, Chittilappilly, Kerala, India.
Article Information
- DOI
- No DOI
- Organised By
- IES College of Engineering
- Conference Date
- 15 May 2023
- Pages
- 65-68
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
[1] J. Miranda, N. Makitalo, J. Garcia-Alonso, J. Berrocal, T. Mikkonen, C. Canal, and J. M. Murillo, “From the internet of things to the
internet of people,” IEEE Internet Computing, vol. 19, no. 2, pp. 40–47, 2015.
[2] T. Qiu, A. Zhao, F. Xia, W. Si, and D. O. Wu, “Rose: Robustness strategy for scale-free wireless sensor networks,” IEEE/ACM
Transactions on Networking, vol. 25, no. 5, pp. 2944–2959, 2017.
[3] L. Yao, Q. Z. Sheng, and S. Dustdar, “Web-based management of the internet of things,” IEEE Internet Computing, vol. 19, no. 4, pp.
60–67, 2015.
[4] T. Qiu, R. Qiao, and D. O. Wu, “Eabs: An event-aware backpressure scheduling scheme for emergency internet of things,” IEEE
Transactions on Mobile Computing, vol. 17, no. 1, pp. 72–84, 2017.[5] T. Qiu, K. Zheng, H. Song, M. Han, and B. Kantarci, “A local-optimization emergency scheduling scheme with self-recovery for smart
grid,” IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3195–3205, 2017.
[6] S. Lu, V. H. Nascimento, J. Sun, and Z. Wang, “Sparsityaware adaptive link combination approach over distributed networks,”
Electronics Letters, vol. 50, no. 18, pp. 1285–1287, 2014.
[7] E. Tan, L. Guo, S. Chen, X. Zhang, and Y. Zhao, “Spammer behavior analysis and detection in user generated content on social
networks,” in IEEE International Conference on Distributed Computing Systems, May. 16-18, 2012, pp. 305–314.
[8] P. Heymann, G. Koutrika, and H. Garcia-Molina, “Fighting spam on social web sites,” IEEE Internet Computing, vol. 11, no. 6, pp. 36–
45, 2007.
[9] M. Al Hasan, V. Chaoji, S. Salem, and M. Zaki, “Link prediction using supervised learning,” in Proc of Sdm Workshop on Link Analysis
Counterterrorism and Security, Apr. 26-28, 2006, pp. 798–805.
[10] F. Pedregosa, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, and J. Vanderplas,
“Scikit-learn: Machine learning in python,” Journal of Machine Learning Research, vol. 12, no. 10, pp. 2825–2830, 2013.
[11] X. Zhu, Y. Nie, S. Jin, A. Li, and Y. Jia, “Spammer detection on online social networks based on logistic regression,” in International
Conference on Web-Age Information Management, Aug. 11-13, 2015, pp. 29–40.
[12] H. Jia, Y. M. Cheung, and J. Liu, “A new distance metric for unsupervised learning of categorical data,” IEEE Transactions on Neural
Networks and Learning Systems, vol. 27, no. 5, pp. 1065–1079, 2016.
[13] S. D. Xenaki, K. D. Koutroumbas, and A. A. Rontogiannis, “A novel adaptive possibilistic clustering algorithm,” IEEE Transactions on
Fuzzy Systems, vol. 24, no. 4, pp. 791–810, 2015.
internet of people,” IEEE Internet Computing, vol. 19, no. 2, pp. 40–47, 2015.
[2] T. Qiu, A. Zhao, F. Xia, W. Si, and D. O. Wu, “Rose: Robustness strategy for scale-free wireless sensor networks,” IEEE/ACM
Transactions on Networking, vol. 25, no. 5, pp. 2944–2959, 2017.
[3] L. Yao, Q. Z. Sheng, and S. Dustdar, “Web-based management of the internet of things,” IEEE Internet Computing, vol. 19, no. 4, pp.
60–67, 2015.
[4] T. Qiu, R. Qiao, and D. O. Wu, “Eabs: An event-aware backpressure scheduling scheme for emergency internet of things,” IEEE
Transactions on Mobile Computing, vol. 17, no. 1, pp. 72–84, 2017.[5] T. Qiu, K. Zheng, H. Song, M. Han, and B. Kantarci, “A local-optimization emergency scheduling scheme with self-recovery for smart
grid,” IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 3195–3205, 2017.
[6] S. Lu, V. H. Nascimento, J. Sun, and Z. Wang, “Sparsityaware adaptive link combination approach over distributed networks,”
Electronics Letters, vol. 50, no. 18, pp. 1285–1287, 2014.
[7] E. Tan, L. Guo, S. Chen, X. Zhang, and Y. Zhao, “Spammer behavior analysis and detection in user generated content on social
networks,” in IEEE International Conference on Distributed Computing Systems, May. 16-18, 2012, pp. 305–314.
[8] P. Heymann, G. Koutrika, and H. Garcia-Molina, “Fighting spam on social web sites,” IEEE Internet Computing, vol. 11, no. 6, pp. 36–
45, 2007.
[9] M. Al Hasan, V. Chaoji, S. Salem, and M. Zaki, “Link prediction using supervised learning,” in Proc of Sdm Workshop on Link Analysis
Counterterrorism and Security, Apr. 26-28, 2006, pp. 798–805.
[10] F. Pedregosa, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, and J. Vanderplas,
“Scikit-learn: Machine learning in python,” Journal of Machine Learning Research, vol. 12, no. 10, pp. 2825–2830, 2013.
[11] X. Zhu, Y. Nie, S. Jin, A. Li, and Y. Jia, “Spammer detection on online social networks based on logistic regression,” in International
Conference on Web-Age Information Management, Aug. 11-13, 2015, pp. 29–40.
[12] H. Jia, Y. M. Cheung, and J. Liu, “A new distance metric for unsupervised learning of categorical data,” IEEE Transactions on Neural
Networks and Learning Systems, vol. 27, no. 5, pp. 1065–1079, 2016.
[13] S. D. Xenaki, K. D. Koutroumbas, and A. A. Rontogiannis, “A novel adaptive possibilistic clustering algorithm,” IEEE Transactions on
Fuzzy Systems, vol. 24, no. 4, pp. 791–810, 2015.
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