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Revealing hidden context: improving mental models of personal firewall users
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ACM International Conference Proceeding Series archive
Proceedings of the 5th Symposium on Usable Privacy and Security table of contents
Mountain View, California
SESSION: Mental models table of contents
Article No. 1  
Year of Publication: 2009
ISBN:978-1-60558-736-3
Authors
Fahimeh Raja  University of British Columbia, Vancouver, Canada
Kirstie Hawkey  University of British Columbia, Vancouver, Canada
Konstantin Beznosov  University of British Columbia, Vancouver, Canada
Sponsors
: Carnegie Mellon CyLab
: Google
Publisher
ACM  New York, NY, USA
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ABSTRACT

The Windows Vista personal firewall provides its diverse users with a basic interface that hides many operational details. However, concealing the impact of network context on the security state of the firewall may result in users developing an incorrect mental model of the protection provided by the firewall. We present a study of participants' mental models of Vista Firewall (VF). We investigated changes to those mental models and their understanding of the firewall's settings after working with both the VF basic interface and our prototype. Our prototype was designed to support development of a more contextually complete mental model through inclusion of network location and connection information. We found that participants produced richer mental models after using the prototype than when working with the VF basic interface; they were also significantly more accurate in their understanding of the configuration of the firewall. Based on our results, we discuss methods of improving user understanding of underlying system states by revealing hidden context, while considering the tension between complexity of the interface and security of the system.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Fahimeh Raja: colleagues
Kirstie Hawkey: colleagues
Konstantin Beznosov: colleagues