01311nas a2200157   4500008004100000020002200041245005100063210005100114260003600165520081800201100001701019700002801036700001501064700002001079856005401099       2009                        eng d  a978-1-4244-2308-800aEmail Shape Analysis for Spam Botnet Detection0 aEmail Shape Analysis for Spam Botnet Detection  aPiscataway, NJ, USAbIEEE Press3 a<p>Botnets have become the major sources of spamming, which generates massive unwanted traffic on networks. An effective detection mechanism can greatly mitigate the problem. In this paper, we present a novel botnet detection mechanism based on the email "shape" analysis that relies on neither content nor reputation analysis. Shape is our new way of characterizing an email by mimicking human visual inspection. A set of email shapes are derived and then used to generate a botnet signature. Our preliminary results show greater than 80% classification accuracy (without considering email content or reputation analysis). This work investigates the discriminatory power of email shape, for which we believe will be a significant complement to other existing techniques such as a network behavior analysis.</p>
1 aSroufe, Paul1 aPhithakkitnukoon, Santi1 aDantu, Ram1 aCangussu, João  uhttp://dl.acm.org/citation.cfm?id=1700527.1700792