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Spyware Prevention by Classifying End User License Agreements
Responsible organisation
2008 (English)Conference paper, (Refereed) Published
Abstract [en]

We investigate the hypothesis that it is possible to detect from the End User License Agreement (EULA) if the associated software hosts spyware. We apply 15 learning algorithms on a, data set consisting of 100 applications with classified EULAs. The results show that 13 algorithms are significantly more accurate than random guessing. Thus, we conclude that the hypothesis can be accepted. Based on the results, we present a novel tool that can be used to prevent spyware by automatically halting application installers and classifying the EULA, giving users the opportunity to make an informed choice about whether to continue with the installation. We discuss positive and negative aspects of this prevention approach and suggest a method for evaluating candidate algorithms for a future implementation.

Place, publisher, year, edition, pages
Wroclaw, POLAND: SPRINGER , 2008.
Keyword [en]
EULA spyware classification prevention
National Category
Computer Science
Identifiers
URN: urn:nbn:se:bth-8112ISI: 000260074000036Local ID: oai:bth.se:forskinfo64C7FD82ABEDB805C12575B000215483ISBN: 978-3-540-79354-0 (print)OAI: oai:DiVA.org:bth-8112DiVA: diva2:835801
Conference
21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems
Available from: 2012-09-18 Created: 2009-05-08 Last updated: 2015-06-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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