Formal Mental Models for Inclusive Privacy and Security


Adam M. Houser and Matthew L. Bolton, Ph.D. University at Buffalo, State University of New York


Efforts to bring inclusive privacy and security solutions to disadvantaged populations will require multifaceted approaches. A key aspect of this challenge is understanding the diverse needs of the userbase, as this will help ensure the alignment of proposed solutions with these needs. One potential strategy for addressing this challenge is to rigorously explore the mental models that characterize stakeholders' privacy and security concerns. This paper will suggest a strategy to meet this challenge, drawing on approaches from human factors engineering and formal methods to establish a framework for modeling and exploring user mental models within a security context. Potential areas of exploration using this method will also be discussed.

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@inproceedings {205683,
title = {Formal Mental Models for Inclusive Privacy and Security},
booktitle = {Thirteenth Symposium on Usable Privacy and Security ({SOUPS} 2017)},
year = {2017},
address = {Santa Clara, CA},
url = {},
publisher = {{USENIX} Association},