An empirical study of spam traffic and the use of DNS black lists
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Understanding the network-level behavior of spammers
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Content based SMS spam filtering
Proceedings of the 2006 ACM symposium on Document engineering
Feature engineering for mobile (SMS) spam filtering
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Characterizing botnets from email spam records
LEET'08 Proceedings of the 1st Usenix Workshop on Large-Scale Exploits and Emergent Threats
Email Spam Filtering: A Systematic Review
Foundations and Trends in Information Retrieval
Social networks and context-aware spam
Proceedings of the 2008 ACM conference on Computer supported cooperative work
A behavior-based SMS antispam system
IBM Journal of Research and Development
The curse of 140 characters: evaluating the efficacy of SMS spam detection on android
Proceedings of the Third ACM workshop on Security and privacy in smartphones & mobile devices
SEC'13 Proceedings of the 22nd USENIX conference on Security
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The Short Messaging Service (SMS), one of the most successful cellular services, generates millions of dollars in revenue for mobile operators. Estimates indicate that billions of text messages are traveling the airwaves daily. Nevertheless, text messaging is becoming a source of customer dissatisfaction due to the rapid surge of messaging abuse activities. Although spam is a well tackled problem in the email world, SMS spam experiences a yearly growth larger than 500%. In this paper we present, to the best of our knowledge, the first analysis of SMS spam traffic from a tier-1 cellular operator. Communication patterns of spammers are compared to those of legitimate cell-phone users and Machine to Machine (M2M) connected appliances. The results indicate that M2M systems exhibit communication profiles similar to spammers, which could mislead spam filters. Beyond the expected results, such as a large load of text messages sent out to a wide target list, other interesting findings are made. For example, the results indicate that the great majority of the spammers connect to the network with just a handful of different hardware models. We find the main geographical sources of messaging abuse in the US. We also find evidence of spammer mobility, voice and data traffic resembling the behavior of legitimate customers.