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VERSION:2.0
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SUMMARY:Network-Level Spam and Scam Defenses
DTSTART:20090615T151500
DTSTAMP:20260413T152907Z
UID:6ad6fbab0ade1815de2f06ef4d9db093c0125f8c0254443e04bdeb02
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Nick Feamster\, Georgia Tech\, College of Computing\, US
 A\nThis talk introduces a new class of methods called "behavioral blacklis
 ting"\, which identify spammers based on their network-level behavior. Rat
 her than attempting to blacklist individual spam messages based on what th
 e message contains\, behavioral blacklisting classifies a message based on
  how the message itself was sent (spatial and temporal traffic patterns of
  the email traffic itself). Behavioral blacklisting tracks the sending beh
 avior of an email sender from a wide variety of vantage points and establi
 shes "fingerprints" that are indicative of spamming behavior. Behavioral b
 lacklisting can apply not only to email traffic\, but also to the network-
 level behavior of hosting infrastructure for scam or phishing attacks. Fir
 st\, I will present a brief overview of our study of the network-level beh
 avior of spammers. Second\, I will describe two behavioral blacklisting al
 gorithms that are based on insights from our study of the network-level be
 havior of spammers. Third\, I will describe SpamSpotter\, a real-time repu
 tation system that integrates these algorithms. Finally\, I will describe 
 our ongoing work applying similar behavioral detection techniques to detec
 ting both online scam hosting infrastructure and phishing attacks. \nProf.
  Feamster's homepage
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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