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Understanding the network-level behavior of spammers
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Source Applications, Technologies, Architectures, and Protocols for Computer Communication archive
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications table of contents
Pisa, Italy
SESSION: Security table of contents
Pages: 291 - 302  
Year of Publication: 2006
ISBN:1-59593-308-5
Also published in ...
Authors
Anirudh Ramachandran  Georgia Tech
Nick Feamster  Georgia Tech
Sponsors
SIGCOMM: ACM Special Interest Group on Data Communication
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 57,   Downloads (12 Months): 419,   Citation Count: 39
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ABSTRACT

This paper studies the network-level behavior of spammers, including: IP address ranges that send the most spam, common spamming modes (e.g., BGP route hijacking, bots), how persistent across time each spamming host is, and characteristics of spamming botnets. We try to answer these questions by analyzing a 17-month trace of over 10 million spam messages collected at an Internet "spam sinkhole", and by correlating this data with the results of IP-based blacklist lookups, passive TCP fingerprinting information, routing information, and botnet "command and control" traces.We find that most spam is being sent from a few regions of IP address space, and that spammers appear to be using transient "bots" that send only a few pieces of email over very short periods of time. Finally, a small, yet non-negligible, amount of spam is received from IP addresses that correspond to short-lived BGP routes, typically for hijacked prefixes. These trends suggest that developing algorithms to identify botnet membership, filtering email messages based on network-level properties (which are less variable than email content), and improving the security of the Internet routing infrastructure, may prove to be extremely effective for combating spam.


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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CITED BY  40

Collaborative Colleagues:
Anirudh Ramachandran: colleagues
Nick Feamster: colleagues