• DocumentCode
    3322971
  • Title

    The smuggling theory approach to organized digital crime

  • Author

    Garg, Vaibhav ; Husted, Nathaniel ; Camp, Jean

  • Author_Institution
    Sch. of Inf. & Comput., Indiana Univ., Bloomington, IN, USA
  • fYear
    2011
  • fDate
    7-9 Nov. 2011
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Governments and inter-governmental organizations are developing cross-jurisdictional mechanisms to decrease global digital crime. The underlying assumption is that the loss incurred from ODC decreases social welfare in every jurisdiction. In this paper we test this assumption by using a framework from economic theory that addresses smuggling in the physical world. Using botnets as a case study we argue that ODC is analogous to smuggling. We then enumerate the conditions under which a model of ODC as smuggling leads to an increase in social welfare using a classic economic model of smuggling. Thus, we show that to the extent ODC is comparable to smuggling, there are situations where ODC increases social welfare. This implies that there will always be some jurisdictions or locales where ODC could rationally be supported. One possible policy implication is that jurisdictions should invest in domestic network reliance and securing the machines within their own jurisdictions.
  • Keywords
    computer crime; computer network security; government data processing; ODC model; botnets; classic economic model; cross jurisdictional mechanism; domestic network reliance; economic theory; global digital crime; government organization; intergovernmental organization; organized digital crime; policy implication; smuggling theory approach; social welfare;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    eCrime Researchers Summit (eCrime), 2011
  • Conference_Location
    San Diego, CA
  • ISSN
    2159-1237
  • Print_ISBN
    978-1-4577-1340-8
  • Electronic_ISBN
    2159-1237
  • Type

    conf

  • DOI
    10.1109/eCrime.2011.6151980
  • Filename
    6151980