Information Security at Large Public Displays

Information Security at Large Public Displays

Carsten Röcker, Carsten Magerkurth, Steve Hinske
DOI: 10.4018/978-1-60566-132-2.ch028
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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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2. Formative Evaluation Of User Requirements

In order to provide trusted mechanisms for privacy protection, it is most crucial to involve potential users in the design process right away from the beginning. Therefore, the requirements of potential users regarding privacy and security issues in multi-user situations were analyzed in two questionnaire-based evaluations.

Key Terms in this Chapter

Smart Artifacts: The notion of ‘Smart Artifacts’ describes technology-enhanced everyday objects, which are equipped with sensors, memory and communication capabilities (see, e.g., Ferguson, 2003 or Gellersen et al., 2000). Hence, they are able to capture information about their surrounding, communicate with each other and react according to previously defined rules (Schoch and Strassner, 2003). Through the capability to interact with humans directly, they can help users to accomplish their tasks in new, intuitive ways (Bohn et al., 2004; 2005). The terms ‘Smart Objects’ and ‘Intelligent Objects’ are synonymously used and describe the same underlying concepts.

Informational Privacy: The term privacy dates back to 1450 (see Feith, 2003) and is constantly adjusted to the needs of a changing society. In its original meaning, the term privacy referred to a state of ‘being apart or belonging to oneself’, in contrast to belonging to the state. When the term privacy is used today, especially in relation with information and communication technology, it usually refers to the concept of informational privacy. One of the most popular definitions is probably the one by Westin (1967), who defined privacy as ‘the claim of individuals, groups or institutions to determine for themselves when, how and to what extend information about them is communicated to others’. In this context, the term informational privacy refers to all data about a person, in general everything other people know about a person, and especially includes individual-related data (von Locquenghien, 2006).

Smart Environments: Based on the initial idea of Ubiquitous Computing (Weiser, 1991), the concept of ‘Smart Environments’ envisions a future, where a multitude of computers are seamlessly embedded into everyday objects of the physical world. In this sense, Cook and Das (2004) define a smart environment as “a small world, where all kinds of smart devices are continuously working to make inhabitants’ lives more comfortable”.

Radio Frequency Identification: Radio Frequency Identification (RFID) is a generic term, describing systems which use radio or electromagnetic propagation for contactless identification of tagged objects. RFID systems usually consist of three components: a transponder containing information, an antenna, used to transmit the signals between the reader and the transponder, and a reader that receives data from a transponder and passes the data to a host system for processing.

Ubiquitous Computing: The vision of ‘Ubiquitous Computing’ was first formulated by Weiser (1991), who argues, that computers should be integrated into the physical environment, and hence be effectively invisible to the user, rather than distinct objects on the desktop. Weiser envisioned the omnipresence of tiny, wirelessly interconnected computers, which are embedded into just about any kind of everyday object (Mattern, 2002). Regarding the interaction with ubiquitous computing applications, the user is not necessarily part of each transaction, instead he controls the system from the outside (Tennenhouse, 2000).

Pervasive Computing: The concept of ‘Pervasive Computing’ is very similar to the one of Ubiquitous Computing. But while the term Ubiquitous Computing is mainly used in the academic domain, the notion of Pervasive Computing is mainly used in industry (see, e.g., Burkhardt et al., 2001 or Hansmann et al., 2003). The term was originally coined by IBM and refers to a shift in corporate computing systems (Friedewald et al., 2006). The only difference of both visions is their temporal scope. While Ubiquitous Computing envisions the omnipresent usage of computer-enhanced everyday objects, the focus of Pervasive Computing is on available respectively emerging technologies, like, e.g. mobile commerce applications or web-based business processes (Mattern, 2005).

Proactive Computing: The vision of ‘Proactive Computing’ (Tennenhouse, 2000) goes even beyond those of Ubiquitous and Pervasive Computing. It anticipates future environments, in which networked computers proactively anticipate our needs and, sometimes, take actions on our behalf.

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