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Information Security at Large Public Displays

Information Security at Large Public Displays

Carsten Röcker, Carsten Magerkurth, Steve Hinske
Copyright: © 2009 |Pages: 22
ISBN13: 9781605661322|ISBN10: 1605661325|EISBN13: 9781605661339
DOI: 10.4018/978-1-60566-132-2.ch028
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MLA

Röcker, Carsten, et al. "Information Security at Large Public Displays." Handbook of Research on Social and Organizational Liabilities in Information Security, edited by Manish Gupta and Raj Sharman, IGI Global, 2009, pp. 471-492. https://doi.org/10.4018/978-1-60566-132-2.ch028

APA

Röcker, C., Magerkurth, C., & Hinske, S. (2009). Information Security at Large Public Displays. In M. Gupta & R. Sharman (Eds.), Handbook of Research on Social and Organizational Liabilities in Information Security (pp. 471-492). IGI Global. https://doi.org/10.4018/978-1-60566-132-2.ch028

Chicago

Röcker, Carsten, Carsten Magerkurth, and Steve Hinske. "Information Security at Large Public Displays." In Handbook of Research on Social and Organizational Liabilities in Information Security, edited by Manish Gupta and Raj Sharman, 471-492. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-132-2.ch028

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Abstract

In this chapter we present a novel concept for personalized privacy support on large public displays. In the first step, two formative evaluations are conducted in order to analyze the requirements of potential users regarding the protection of private information on large public displays. The insights gained in these evaluations are used to design a system that automatically adapts the information visible on public displays according to the current social situation and the individual privacy preferences of the user working on the display. In a third evaluation, the developed system is evaluated regarding its appropriateness for daily usage and its usefulness to protect privacy. The results of the evaluation show that users are in general willing to trust system-based protection mechanisms, provided that they are well implemented. In this context, the proposed combination of pre-defined privacy profiles and context-adapted information visualization proved to be a good trade-off between usability and adequate privacy protection.

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