@inproceedings{37fab042ecc746099a2158101ce110b6,
title = "Understanding SMS spam in a large cellular network",
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.",
keywords = "Cellular network, Clustering, Detection, SMS spam",
author = "Nan Jiang and Yu Jin and Ann Skudlark and Zhi-Li Zhang",
note = "Copyright: Copyright 2013 Elsevier B.V., All rights reserved.; 2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS 2013 ; Conference date: 17-06-2013 Through 21-06-2013",
year = "2013",
doi = "10.1145/2494232.2465530",
language = "English (US)",
isbn = "9781450319003",
series = "Performance Evaluation Review",
number = "1 SPEC. ISS.",
pages = "381--382",
booktitle = "SIGMETRICS 2013 - Proceedings of the 2013 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems",
edition = "1 SPEC. ISS.",
}