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S-Detector: an enhanced security model for detecting Smishing attack for mobile computing

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Abstract

Recently the mobile computing technology has been generally used to people with the development of the IT technology. The mobile computing environment has provided a convenient environment via the intelligent devices such as tablet PC, smartphone, etc. However, many security threats in the mobile computing environment exist. Therefore, secure elements to protect against security threats are needed. In particular, Short Message Service phishing (Smishing) damage has continued to increase with the normalization of mobile computing environment. We discuss and analyze the security considerations about Smishing in mobile computing environments. In addition, we propose an enhanced security model for detecting Smishing attack (we called “S-Detector”). The proposed model is applied to a Naive Bayes classifier to improve the Smishing attack detection in smart devices. This model distinguishes normal text message and Smishing message. And this is mainly used to filter by using statistical learning method. As a result, it is possible to analyze a text message and effectively detect SMS phishing. Finally, we demonstrate the efficiency of our model through the evaluation and analysis of our proposed model.

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Acknowledgements

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1014) supervised by the IITP (Institute for Information & Communications Technology Promotion)

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Seoul National University of Science and Technology (SeoulTech), Seoul, 139-743, Korea

    Jae Woong Joo, Seo Yeon Moon, Saurabh Singh & Jong Hyuk Park

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  1. Jae Woong Joo
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  2. Seo Yeon Moon
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  3. Saurabh Singh
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  4. Jong Hyuk Park
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Correspondence to Jong Hyuk Park.

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Joo, J.W., Moon, S.Y., Singh, S. et al. S-Detector: an enhanced security model for detecting Smishing attack for mobile computing. Telecommun Syst 66, 29–38 (2017). https://doi.org/10.1007/s11235-016-0269-9

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  • DOI: https://doi.org/10.1007/s11235-016-0269-9

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