Advertisement

Do Graphical Cues Effectively Inform Users?

A Socio-Technical Security Study in Accessing Wifi Networks
  • Ana Ferreira
  • Jean-Louis HuynenEmail author
  • Vincent Koenig
  • Gabriele Lenzini
  • Salvador Rivas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9190)

Abstract

We study whether the padlock and the signal strength bars, two visual cues shown in network managers, convey their intended messages. Since users often choose insecure networks when they should not, finding the answer is not obvious; in our study we clarify whether the problem lies in uninformative and ambiguous cues or in the user who, despite understanding the cues, chooses otherwise. This paper describes experiments and comments the results that bring evidence to our study.

Keywords

Signal Strength Secure Communication Network Selection Good Connectivity Intended Message 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Ferreira, A., Huynen, J.L., Koenig, V., Lenzini, G.: Socio-technical security analysis of wireless hotspots. In: Tryfonas, T., Askoxylakis, I. (eds.) HAS 2014. LNCS, vol. 8533, pp. 306–317. Springer, Heidelberg (2014) Google Scholar
  2. 2.
    Jeske, D., Coventry, L., Briggs, P.: Decision justifications for wireless network selection. In: 2014 Workshop on Socio-Technical Aspects in Security and Trust (STAST), pp. 1–7, July 2014Google Scholar
  3. 3.
    Grice, P.: Studies in the Way of Words. Harvard University Press, Cambridge (1989) Google Scholar
  4. 4.
    Rand, D.G.: The promise of Mechanical Turk: how online labor markets can help theorists run behavioral experiments. J. Theor. Biol. 299, 172–179 (2012)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Paolacci, G., Chandler, J., Ipeirotis, P.: Running experiments on amazon Mechanical Turk. Judgm. Decis. Mak. 5(5), 411–419 (2010)Google Scholar
  6. 6.
    Crump, M.J.C., McDonnell, J.V., Gureckis, T.M.: Evaluating Amazon’s Mechanical Turk as a tool for experimental behavioral research. PLoS One 8(3), e57410 (2013)CrossRefGoogle Scholar
  7. 7.
    We are dynamo turker community: guidelines for academic requesters. http://wearedynamo.org/
  8. 8.
    Bureau, U.S., Statistics, L.: Standard Occupational Classification and Coding Structure, pp. 1–7. Health, San Francisco (2010) Google Scholar
  9. 9.
    U.S. department of the census: current population survey interviewing manual, June 2013Google Scholar
  10. 10.
    Finch, J.: The vignette technique in survey research. Sociology 21(1), 105–114 (1987)CrossRefGoogle Scholar
  11. 11.
    R Development Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2008). http://cran.rproject.org/doc/FAQ/R-FAQ.html#Citing-R
  12. 12.
    Wilcoxon, F.: Individual comparisons by ranking methods. Biom. Bull. 1(6), 80–83 (1945)CrossRefGoogle Scholar
  13. 13.
    McCullagh, P.: Generalized Linear Models. Chapman and Hall, New York (1989) CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ana Ferreira
    • 1
    • 2
  • Jean-Louis Huynen
    • 1
    • 2
    Email author
  • Vincent Koenig
    • 1
    • 2
  • Gabriele Lenzini
    • 2
  • Salvador Rivas
    • 1
  1. 1.Institute of Cognitive Science and AssessmentUniversity of LuxembourgLuxembourgLuxembourg
  2. 2.Interdisciplinary Centre for Security Reliability and TrustUniversity of LuxembourgLuxembourgLuxembourg

Personalised recommendations