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Property Analysis of SMS Spam Using Text Mining

  • Conference paper
  • First Online:
Advanced Multimedia and Ubiquitous Engineering (FutureTech 2017, MUE 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 448))

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Abstract

A considerable amount of spam that occur each year can cause the financial damage as well as mental harm to the recipient. This is a serious problem in society. In this paper, we analyze properties of SMS spam in mobile phones to establish a method for effectively blocking SMS spam. As a result, SMS spam can be seen that the surge in the amount shipped during a specific time period. Also, we could find the frequently included word on spam and we could identify spammer that sent smishing messages frequently by comparing several spammers.

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References

  1. Ministry of Science, ICT and Future Planning: The current status of wireless communication service users as of May 2016, 30 May 2016. http://www.msip.go.kr/

  2. Park, I.W., Park, D.W.: A study on the analysis and security measures for smishing hacking attacks. J. Next Gen. Inf. Technol. 5(2), 85–91 (2014)

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Acknowledgements

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the University Information Technology Research Center support program (IITP-2016-R2718-16-0003) supervised by the IITP (Institute for Information & communications Technology Promotion).

Author information

Authors and Affiliations

  1. Computer Science Engineering, Chungnam National University, Daejeon, Republic of Korea

    Manki Baek, Youngkyung Lee & Yoojae Won

Authors
  1. Manki Baek
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  2. Youngkyung Lee
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  3. Yoojae Won
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Corresponding author

Correspondence to Yoojae Won .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, Korea (Republic of)

    James J. (Jong Hyuk) Park

  2. School of Computing and Information Sciences, Florida International University, Miami, Florida, USA

    Shu-Ching Chen

  3. Department of Information Systems and Cyber Security, The University of Texas at San Antonio, Adelaide, Australia

    Kim-Kwang Raymond Choo

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© 2017 Springer Nature Singapore Pte Ltd.

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Baek, M., Lee, Y., Won, Y. (2017). Property Analysis of SMS Spam Using Text Mining. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_12

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  • DOI: https://doi.org/10.1007/978-981-10-5041-1_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5040-4

  • Online ISBN: 978-981-10-5041-1

  • eBook Packages: EngineeringEngineering (R0)

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