Title :
Detecting Targeted Malicious Email
Author :
Amin, Rohan M. ; Ryan, Julie J C H ; Van Dorp, J. René
Author_Institution :
George Washington Univ., Washington, DC, USA
Abstract :
Targeted malicious emails (TME) for computer network exploitation have become more insidious and more widely documented in recent years. Beyond spam or phishing designed to trick users into revealing personal information, TME can exploit computer networks and gather sensitive information. They can consist of coordinated and persistent campaigns that can span years. A new email-filtering technique based on email´s persistent-threat and recipient-oriented features with a random forest classifier outperforms two traditional detection methods, SpamAssassin and ClamAV, while maintaining reasonable false positive rates.
Keywords :
computer crime; information filtering; pattern classification; trees (mathematics); unsolicited e-mail; ClamAV; SpamAssassin; computer network exploitation; coordinated campaign; email persistent-threat feature; email-filtering technique; false positive rate; persistent campaign; personal information; phishing; random forest classifier; recipient-oriented feature; sensitive information; spam; targeted malicious email detection; Computer security; Electronic mail; Feature extraction; Google; Internet; Unsolicited electronic mail; TME spear phishing; email; recipient; spam; targeted attacks; threat;
Journal_Title :
Security & Privacy, IEEE
DOI :
10.1109/MSP.2011.154