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Botnet spam campaigns can be long lasting: evidence, implications, and analysis
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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems table of contents
Seattle, WA, USA
SESSION: Security table of contents
Pages 13-24  
Year of Publication: 2009
ISBN:978-1-60558-511-6
Authors
Abhinav Pathak  Purdue University, West Lafayette, USA
Feng Qian  University of Michigan, Ann Arbor, USA
Y. Charlie Hu  Purdue University, West Lafayette, USA
Z. Morley Mao  University of Michigan, Ann Arbor, USA
Supranamaya Ranjan  Narus, Inc., Mountain View, USA
Sponsors
ACM: Association for Computing Machinery
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
Publisher
ACM  New York, NY, USA
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ABSTRACT

Accurately identifying spam campaigns launched by a large number of bots in a botnet allows for accurate spam campaign signature generation and hence is critical to defeating spamming botnets. The straight-forward approach of clustering all spam containing the same label such as an URL into a campaign can be easily defeated by techniques such as simple obfuscations of URLs. In this paper, we perform a comprehensive study of content-agnostic characteristics of spam campaigns, e.g. duration and source-network distribution of spammers, in order to ascertain whether and how they can assist the simple label-based clustering methods in identifying campaigns and generating campaign signatures. In particular, from a five-month trace collected by a relay sinkhole, we manually identified and then analyzed seven URL-based botnet spam campaigns consisting of 52 million spam messages sent over 2.09 million SMTP connections originated from over 150,000 non-proxy spamming hosts and destined to about 200,000 end domains. Our analysis shows that the spam campaigns, when observed from large destination domains, exhibit durations far longer than the five-day period as reported in a recent study. We analyze the implications of this finding on spam campaign signature generation. We further study other characteristics of these long-lasting campaigns. Our analysis reveals several new findings regarding workload distribution, sending patterns, and coordination among the spamming machines.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Route Views Project Page. http://www.routeviews.org.
 
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Bl: Spamcop blocking list. http://bl.spamcop.net.
 
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Cbl: Composite blocking list. http://cbl.abuseat.org/.
 
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R. Clayton. Do zebras get more spam than aardvarks? In Proc. of CEAS, 2008.
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Sorbs: Spam and open-relay blocking system. http://dnsbl.sorbs.net.
 
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Dsbl: Distributed sender blackhole list. list.dsbl.org.
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Maxmind -- ip geolocation and online fraud prevention. http://www.maxmind.com/.
 
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Njabl: Spam blocking blacklist. http://www.njabl.org/.
 
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Pbl: The policy block list. http://www.spamhaus.org/pbl/.
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Super webscan. http://www.sharewareconnection.com/super-webscan.htm.
 
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Joe st sauver: Evolving methods for sending spam and malware. http://www.ftc.gov/bcp/workshops/spamsummit/presentations/Evolving-Methods.pdf.
 
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The spamhaus project. sbl-xbl.spamhaus.org.
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2006 spam trends report: Year of the zombies. http://www.commtouch.com/downloads/Commtouch_2006_Spam_Trends_Year_of_the_Zombies.pdf.

Collaborative Colleagues:
Abhinav Pathak: colleagues
Feng Qian: colleagues
Y. Charlie Hu: colleagues
Z. Morley Mao: colleagues
Supranamaya Ranjan: colleagues