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Thwarting E-mail Spam Laundering
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ACM Transactions on Information and System Security (TISSEC) archive
Volume 12 ,  Issue 2  (December 2008) table of contents
Article No. 13  
Year of Publication: 2008
ISSN:1094-9224
Authors
Mengjun Xie  College of William and Mary
Heng Yin  College of William and Mary
Haining Wang  College of William and Mary
Publisher
ACM  New York, NY, USA
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ABSTRACT

Laundering e-mail spam through open-proxies or compromised PCs is a widely-used trick to conceal real spam sources and reduce spamming cost in the underground e-mail spam industry. Spammers have plagued the Internet by exploiting a large number of spam proxies. The facility of breaking spam laundering and deterring spamming activities close to their sources, which would greatly benefit not only e-mail users but also victim ISPs, is in great demand but still missing. In this article, we reveal one salient characteristic of proxy-based spamming activities, namely packet symmetry, by analyzing protocol semantics and timing causality. Based on the packet symmetry exhibited in spam laundering, we propose a simple and effective technique, DBSpam, to online detect and break spam laundering activities inside a customer network. Monitoring the bidirectional traffic passing through a network gateway, DBSpam utilizes a simple statistical method, Sequential Probability Ratio Test, to detect the occurrence of spam laundering in a timely manner. To balance the goals of promptness and accuracy, we introduce a noise-reduction technique in DBSpam, after which the laundering path can be identified more accurately. Then DBSpam activates its spam suppressing mechanism to break the spam laundering. We implement a prototype of DBSpam based on libpcap, and validate its efficacy on spam detection and suppression through both theoretical analyses and trace-based experiments.


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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Collaborative Colleagues:
Mengjun Xie: colleagues
Heng Yin: colleagues
Haining Wang: colleagues