A Study on Spam Detection Methods for Safe SMS Communication

  • Authors

    • Shailee Bhatia
    • . .
    2018-07-20
    https://doi.org/10.14419/ijet.v7i3.12.16502
  • Filtration, SMS, Spam.

  • Abstract

    The electronic communication enables the instant and all type availability of user. The different form of information transition can be drawn in the form of SMS and emails. But these emails and SMS systems are also used by the individuals and firm as medium of their advertisement. Spam messages not only involves the unwanted messages but it also includes some viruses and threat to the security system. In this paper, a study to the SMS filtration methods is provided. The paper has explored the types of SMS spams, its threats and various filtration methods to detect the spam SMS.

     

     

  • References

    1. [1] “SMS Spam Overview — Preserving the value of SMS textingâ€, https://www.cloudmark.com/en/s/resources/whitepapers/sms-spam-overview

      [2] Cormack, G. V., Hidalgo, J. M. G., & Sánz, E. P. (2007, July). Feature engineering for mobile (SMS) spam filtering. In Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval (pp. 871-872). ACM.

      [3] Ramachandran, A., Feamster, N., & Vempala, S. (2007, October). Filtering spam with behavioral blacklisting. In Proceedings of the 14th ACM conference on Computer and communications security (pp. 342-351). ACM.

      [4] Yadav, K., Kumaraguru, P., Goyal, A., Gupta, A., & Naik, V. (2011, March). Smsassassin: Crowdsourcing driven mobile-based system for sms spam filtering. In Proceedings of the 12th Workshop on Mobile Computing Systems and Applications (pp. 1-6). ACM.

      [5] Gómez Hidalgo, J. M., Bringas, G. C., Sánz, E. P., & García, F. C. (2006, October). Content based SMS spam filtering. In Proceedings of the 2006 ACM symposium on Document engineering (pp. 107-114). ACM.

      [6] Kolcz, A., Bond, M., & Sargent, J. (2006, May). The challenges of service-side personalized spam filtering: scalability and beyond. In Proceedings of the 1st international conference on Scalable information systems (p. 21). ACM.Pattaraporn Klangpraphant," E-Mail Authentication System: A Spam Filtering for Smart Senders", ICIS 2009, November 24-26, 2009 Seoul, Korea ACM 978-1-60558-710-3/09/11

      [7] Klangpraphant, P., & Bhattarakosol, P. (2009, November). E-mail authentication system: a spam filtering for smart senders. In Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human (pp. 534-538). ACM.

      [8] Erdélyi, M., Benczúr, A. A., Masanés, J., & Siklósi, D. (2009, April). Web spam filtering in internet archives. In Proceedings of the 5th international workshop on Adversarial information retrieval on the web (pp. 17-20). ACM.

      [9] Laorden, C., Ugarte-Pedrero, X., Santos, I., Sanz, B., & Bringas, P. G. (2011, September). Enhancing scalability in anomaly-based email spam filtering. In Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference (pp. 13-22). ACM.

      [10] Dasgupta, A., Gurevich, M., & Punera, K. (2011, February). Enhanced email spam filtering through combining similarity graphs. In Proceedings of the fourth ACM international conference on Web search and data mining (pp. 785-794). ACM.

      [11] Whissell, J. S., & Clarke, C. L. (2011, September). Clustering for semi-supervised spam filtering. In Proceedings of the 8th Annual Collaboration, Electronic messaging, Anti-Abuse and Spam Conference (pp. 125-134). ACM.

      [12] Ming-wei Chang," Partitioned Logistic Regression for Spam Filtering", KDD’08, August 24–27, 2008, Las Vegas, Nevada, USA. ACM 978-1-60558-193-4/08/08

      [13] Almeida, T. A., Yamakami, A., & Almeida, J. (2010, March). Filtering spams using the minimum description length principle. In Proceedings of the 2010 ACM Symposium on Applied Computing (pp. 1854-1858). ACM.

      [14] Almeida, T. A., Hidalgo, J. M. G., & Yamakami, A. (2011, September). Contributions to the study of SMS spam filtering: new collection and results. In Proceedings of the 11th ACM symposium on Document engineering (pp. 259-262). ACM.

      [15] Youn, S., & McLeod, D. (2009, March). Improved spam filtering by extraction of information from text embedded image e-mail. In Proceedings of the 2009 ACM symposium on Applied Computing (pp. 1754-1755). ACM.

      [16] Caruana, G., & Li, M. (2012). A survey of emerging approaches to spam filtering. ACM Computing Surveys (CSUR), 44(2), 9.

      [17] Munro, R., & Manning, C. D. (2012, March). Short message communications: users, topics, and in-language processing. In Proceedings of the 2nd ACM Symposium on Computing for Development (p. 4). ACM.

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  • How to Cite

    Bhatia, S., & ., . (2018). A Study on Spam Detection Methods for Safe SMS Communication. International Journal of Engineering & Technology, 7(3.12), 790-792. https://doi.org/10.14419/ijet.v7i3.12.16502

    Received date: 2018-07-29

    Accepted date: 2018-07-29

    Published date: 2018-07-20