Increasing Service Users’ Privacy Awareness by Introducing On-Line Interactive Privacy Features

Kani‐Zabihi, Elahe; Helmhout, Martin

doi:10.1007/978-3-642-29615-4_10

Cited by 26 publications

(26 citation statements)

References 18 publications

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“…The Interfaces category refers to both visualisations and user interface developments. Kani-Zabihi and Helmhout [31] discussed online interactive privacy features; tools designed to support user decision-making. They described an enquiry system which helps individuals discuss their privacy concerns with service providers.…”

Section: Theme Taxonomymentioning

confidence: 99%

Privacy Salience: Taxonomies and Research Opportunities

Williams

Nurse

Creese

2016

Privacy and Identity Management. Facing Up to Next Steps

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Privacy is a well-understood concept in the physical world, with us all desiring some escape from the public gaze. However, while individuals might recognise locking doors as protecting privacy, they have difficulty practising equivalent actions online. Privacy salience considers the tangibility of this important principle; one which is often obscured in digital environments. Through extensively surveying a range of studies, we construct the first taxonomies of privacy salience. After coding articles and identifying commonalities, we categorise works by their methodologies, platforms and underlying themes. While web browsing appears to be frequently analysed, the Internet-of-Things has received little attention. Through our use of category tuples and frequency matrices, we then explore those research opportunities which might have been overlooked. These include studies of targeted advertising and its affect on salience in social networks. It is through refining our understanding of this important topic that we can better highlight the subject of privacy.

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Section: Theme Taxonomymentioning

confidence: 99%

Privacy Salience: Taxonomies and Research Opportunities

Williams

Nurse

Creese

2016

Privacy and Identity Management. Facing Up to Next Steps

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“…In particular, Kolter et al [13] proposed displaying personal data disclosures from different comprehensible visualization perspectives, concluding that participants found a graph view useful and intuitive for visualizing online relationships. Similarly, the VOME project [12] studied a so-called 'interactive social translucence map', and Zavou et al [21] explored a 'chord diagram' visualization to inform cloud users and service providers about the way data is exchanged in an online transaction. It has also been suggested in [8] that network visualizations have the potential for scalability and dimensionality often encountered in data related to security monitoring and mitigation.…”

Section: Related Workmentioning

confidence: 99%

Usable Transparency with the Data Track

Angulo

Fischer‐Hübner

Pulls

et al. 2015

Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

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We present a prototype of the user interface of a transparency tool that displays an overview of a user's data disclosures to different online service providers and allows them to access data collected about them stored at the services' sides. We explore one particular type of visualization method consisting of tracing lines that connect a user's disclosed personal attributes to the service to which these attributes have been disclosed. We report on the ongoing iterative process of design of such visualization, the challenges encountered and the possibilities for future improvements.

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“…5.8.1 [17]. Besides, previous research studies suggest that network-like visualizations provide a simple way to understand the meaning behind some types of data [48,49], and other recent studies claim that users appreciate graphical representations of their personal data flows in forms of links and nodes [50,51]. The results of usability evaluations that we performed in A4Cloud for graphical user interfaces of the Data Track trace view as depicted in Fig.…”

Section: Controlled Experimentsmentioning

confidence: 99%

HCI Requirements for Transparency and Accountability Tools for Cloud Service Chains

Fischer‐Hübner

Pettersson

Angulo

2015

Lecture Notes in Computer Science

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Abstract. This paper elaborates HCI (Human-Computer Interaction) requirements for making cloud data protection tools comprehensible and trustworthy. The requirements and corresponding user interface design principles are derived from our research and review work conducted to address in particular the following HCI challenges: How can the users be guided to better comprehend the flow and traces of data on the Internet and in the cloud? How can individual end users be supported to do better informed decisions on how their data can be used by cloud providers or others? How can the legal privacy principle of transparency and accountability be enforced by the user interfaces of cloud inspection tools? How can the user interfaces help users to reassess their trust/distrust in services? The research methods that we have used comprise stakeholder workshops, focus groups, controlled experiments, usability tests as well as literature and law reviews. The derived requirements and principles are grouped into the following functional categories: (1) ex-ante transparency, (2) exercising data subject rights, (3) obtaining consent, (4) privacy preference management, (5) privacy policy management, (6) ex-post transparency, (7) audit configuration, (8) access control management, and (9) privacy risk assessment. This broad categorization makes our results accessible and applicable for any developer within the field of usable privacy and transparency-enhancing technologies for cloud service chains.

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Increasing Service Users’ Privacy Awareness by Introducing On-Line Interactive Privacy Features

Cited by 26 publications

References 18 publications

Privacy Salience: Taxonomies and Research Opportunities

Privacy Salience: Taxonomies and Research Opportunities

Usable Transparency with the Data Track

HCI Requirements for Transparency and Accountability Tools for Cloud Service Chains

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