Spam Classification Based on E-Mail Path Analysis
Srikanth Palla,
Ram Dantu and
João W. Cangussu
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Srikanth Palla: University of North Texas, USA
Ram Dantu: University of North Texas, USA
João W. Cangussu: University of Texas at Dallas, USA
International Journal of Information Security and Privacy (IJISP), 2008, vol. 2, issue 2, 46-69
Abstract:
Email spam is the most effective form of online advertising. Unlike telephone marketing, email spamming does not require huge human or financial resources investment. Most existing spam filtering techniques concentrate on the emails’ content. However, most spammers obfuscate their emails’ content to circumvent content-based spam filters. An integrated solution for restricting spam emails is needed as content analyses alone might not provide a solution for filtering unsolicited emails. Here we present a new method for isolating unsolicited emails. Though spammers obfuscate their emails’ content, they do not have access to all the fields in the email header. Our classification method is based on the path an email traverses instead of content. Overall, our classifier produced fewer false positives when compared to current filters such as SpamAssassin. We achieved a precision of 98.65% which compares well with the precisions achieved by SPF, DNSRBL blacklists.
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jisp00:v:2:y:2008:i:2:p:46-69
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International Journal of Information Security and Privacy (IJISP) is currently edited by Yassine Maleh
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