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Financial Lower Bounds of Online Advertising Abuse

A Four Year Case Study of the TDSS/TDL4 Botnet
  • Yizheng ChenEmail author
  • Panagiotis Kintis
  • Manos Antonakakis
  • Yacin Nadji
  • David Dagon
  • Wenke Lee
  • Michael Farrell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9721)

Abstract

Online advertising is a complex on-line business, which has become the target of abuse. Recent charges filed from the United States Department of Justice against the operators of the DNSChanger botnet stated that the botnet operators stole approximately US $14 million [11, 18] over two years. Using monetization tactics similar to DNSChanger, several large botnets (i.e., ZeroAccess and TDSS/TDL4) abuse the ad ecosystem at scale. In order to understand the depth of the financial abuse problem, we need methods that will enable us to passively study large botnets and estimate the lower bounds of their financial abuse. In this paper we present a system, \(A^{2}S\), which is able to analyze one of the most complex, sophisticated, and long-lived botnets: TDSS/TDL4. Using passive datasets from a large Internet Service Provider in north America, we conservatively estimate lower bounds behind the financial abuse TDSS/TDL4 inflicted on the advertising ecosystem since 2010. Over its lifetime, less than 15 % of the botnet’s victims caused at least US$346 million in damages to advertisers due to impression fraud. TDSS/TDL4 abuse translates to an average US$340 thousand loss per day to advertisers, which is three times the ZeroAccess botnet [27] and more than ten times the DNSChanger botnet [2] estimates of fraud.

Notes

Acknowledgements

The authors would like to thank Dr. Brett Stone-Gross and Dag Liodden for their comments and feedback. This material is based upon work supported in part by the US Department of Commerce under grant no. 2106DEK and Georgia Tech Research Institute (GTRI) IRAD grant no. 21043091. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the US Department of Commerce nor GTRI.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Yizheng Chen
    • 1
    Email author
  • Panagiotis Kintis
    • 1
  • Manos Antonakakis
    • 2
  • Yacin Nadji
    • 1
  • David Dagon
    • 1
  • Wenke Lee
    • 1
  • Michael Farrell
    • 3
  1. 1.School of Computer ScienceGeorgia Institute of TechnologyAtlantaUSA
  2. 2.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA
  3. 3.Institute for Internet Security and PrivacyGeorgia Institute of TechnologyAtlantaUSA

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