• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Abstract Spamscatter: Characterizing Internet Scam Hosting Infrastructure

Cached

  • Download as a PDF

Download Links

  • [www.ics.uci.edu]
  • [www.cs.duke.edu]
  • [www.usenix.org]
  • [www.usenix.org]
  • [www-cse.ucsd.edu]
  • [www.cs.ucsd.edu]
  • [www.cs.ucsd.edu]
  • [www.cse.ucsd.edu]
  • [www.cs.ucsd.edu]
  • [www-cse.ucsd.edu]
  • [sysnet.ucsd.edu]
  • [www.cse.ucsd.edu]
  • [cseweb.ucsd.edu]
  • [cseweb.ucsd.edu]
  • [cseweb.ucsd.edu]
  • [www.csd.uoc.gr]
  • [www.cs.duke.edu]
  • [www.cs.duke.edu]
  • [www.sysnet.ucsd.edu]
  • [sysnet.ucsd.edu]
  • [cseweb.ucsd.edu]
  • [cseweb.ucsd.edu]
  • [www.csd.uoc.gr]

  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by David S. Anderson , Chris Fleizach , Stefan Savage , Geoffrey M. Voelker
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@MISC{Anderson_abstractspamscatter:,
    author = {David S. Anderson and Chris Fleizach and Stefan Savage and Geoffrey M. Voelker},
    title = {Abstract Spamscatter: Characterizing Internet Scam Hosting Infrastructure},
    year = {}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Unsolicited bulk e-mail, or SPAM, is a means to an end. For virtually all such messages, the intent is to attract the recipient into entering a commercial transaction — typically via a linked Web site. While the prodigious infrastructure used to pump out billions of such solicitations is essential, the engine driving this process is ultimately the “point-of-sale ” — the various money-making “scams” that extract value from Internet users. In the hopes of better understanding the business pressures exerted on spammers, this paper focuses squarely on the Internet infrastructure used to host and support such scams. We describe an opportunistic measurement technique called spamscatter that mines emails in real-time, follows the embedded link structure, and automatically clusters the destination Web sites using image shingling to capture graphical similarity between rendered sites. We have implemented this approach on a large real-time spam feed (over 1M messages per week) and have identified and analyzed over 2,000 distinct scams on 7,000 distinct servers. 1

Keyphrases

abstract spamscatter    characterizing internet scam hosting infrastructure    graphical similarity    opportunistic measurement technique    internet infrastructure    distinct server    unsolicited bulk e-mail    various money-making scam    distinct scam    embedded link structure    destination web    commercial transaction    internet user    web site    prodigious infrastructure    business pressure    large real-time spam feed   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University