Understanding SMS spam in a large cellular network

Nan Jiang, Yu Jin, Ann Skudlark, Zhi-Li Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we conduct a comprehensive study of SMS spam in a large cellular network in the US. Using one year of user reported spam messages to the network carrier, we devise text clustering techniques to group associated spam messages in order to identify SMS spam campaigns and spam activities. Our analysis shows that spam campaigns can last for months and have a wide impact on the cellular network. Combining with SMS network records collected during the same time, we f nd that spam numbers within the same activity often exhibit strong similarity in terms of their sending patterns, tenure and geolocations. Our analysis sheds light on the intentions and strategies of SMS spammers and provides unique insights in developing better method for detecting SMS spam.

Original languageEnglish (US)
Title of host publicationSIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
Pages381-382
Number of pages2
Edition1 SPEC. ISS.
DOIs
StatePublished - 2013
Event2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013 - Pittsburgh, PA, United States
Duration: Jun 17 2013Jun 21 2013

Publication series

NamePerformance Evaluation Review
Number1 SPEC. ISS.
Volume41
ISSN (Print)0163-5999

Conference

Conference2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013
CountryUnited States
CityPittsburgh, PA
Period6/17/136/21/13

Keywords

  • Cellular network
  • Clustering
  • Detection
  • SMS spam

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