Abstract
Email has become an integral part of everyday life. Without a second thought we receive bills, bank statements, and sales promotions all to our inbox. Each email has hidden features that can be extracted. In this paper, we present a new mechanism to characterize an email without using content or context called Email Shape Analysis. We explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering, and social-context based finger printing. Our in-depth analysis of botnet detection leads to very high accuracy of tracing templates and spam campaigns. However, when it comes to spam filtering we do not propose new method but rather a complementing method to the already high accuracy Bayesian spam filter. We also look at its ability to classify individual senders in personal email inbox’s.
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Sroufe, P., Phithakkitnukoon, S., Dantu, R., Cangussu, J. (2010). Email Shape Analysis. In: Kant, K., Pemmaraju, S.V., Sivalingam, K.M., Wu, J. (eds) Distributed Computing and Networking. ICDCN 2010. Lecture Notes in Computer Science, vol 5935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11322-2_7
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DOI: https://doi.org/10.1007/978-3-642-11322-2_7
Publisher Name: Springer, Berlin, Heidelberg
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