Greystar: Fast and accurate detection of SMS spam numbers in large cellular networks using grey phone space

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

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

24 Scopus citations


In this paper, we present the design of Greystar, an innovative defense system for combating the growing SMS spam traffic in cellular networks. By exploiting the fact that most SMS spammers select targets randomly from the finite phone number space, Greystar monitors phone numbers from the grey phone space (which are associated with data only devices like laptop data cards and machine-to-machine communication devices like electricity meters) and employs a novel statistical model to detect spam numbers based on their footprints on the grey phone space. Evaluation using five month SMS call detail records from a large US cellular carrier shows that Greystar can detect thousands of spam numbers each month with very few false alarms and 15% of the detected spam numbers have never been reported by spam recipients. Moreover, Greystar is much faster in detecting SMS spam than existing victim spam reports, reducing spam traffic by 75% during peak hours.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd USENIX Security Symposium
PublisherUSENIX Association
Number of pages16
ISBN (Electronic)9781931971034
StatePublished - 2013
Event22nd USENIX Security Symposium - Washington, United States
Duration: Aug 14 2013Aug 16 2013

Publication series

NameProceedings of the 22nd USENIX Security Symposium


Conference22nd USENIX Security Symposium
Country/TerritoryUnited States

Bibliographical note

Funding Information:
The work was supported in part by the NSF grants CNS-1017647 and CNS-1117536, the DTRA grant HDTRA1-09-1-0050. We thank Peter Coulter, Cheri Kerstetter and Colin Goodall for their useful discussions and constructive comments. Finally, we thank our shepherd, Patrick Traynor, for his many suggestions on improving the paper.


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