Tracing Personal Data Using Comics

Schreiber, Andreas; Struminski, Regina

doi:10.1007/978-3-319-58706-6_36

Cited by 7 publications

(4 citation statements)

References 17 publications

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“…7 Some of the papers are included in multiple categories due to an overlap in contributions 8 4 of those papers (4/37) were defined as models Next, we discuss the health conditions covered in the included papers, followed by the privacy and security regulations that they refer to. [6], [8], [17], [22], [23], [27], [41], [51]- [68] General focus (n=18) [2], [21], [24] [3], [4], [12], [76], [80], [81], [92], [96]- [110] S/P focused design features and recommendations (n=16) [7], [25], [28], [51], [54], [57], [59], [66], [93]- [95], [111]- [114] 1) Target health conditions…”

Section: Iv1 Study Selection and Data Extractionmentioning

confidence: 99%

Security and Privacy of mHealth Applications: A Scoping Review

2020

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While digital health or mHealth applications (apps) have become accessible resources for the support of personal health, the privacy and security of users' data have been the subject of concern and controversy. As large numbers of mHealth apps are created and are increasingly widely used by people with various health conditions, it is crucial to have clear and valid methods for evaluating the data practices within them. Recent regulatory initiatives such as the European Union's General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) have had the effect of raising awareness and establishing a minimal set of expectations. However, they do not in themselves address the issue of the development of systems which meet privacy and security requirements. There is a growing body of research on evaluation techniques and frameworks to support the assessment of the privacy and security of health apps, and guidelines to support their design. However, it can be challenging to navigate this space and choose appropriate techniques for a given context. Addressing this issue, this paper examines the recent literature on security and privacy of m-Health applications, using a scoping review methodology. It analyses data security and privacy evaluation techniques and frameworks that have been proposed for mHealth applications, as well as relevant research-based design recommendations. This work consolidates recent research on the topic to support researchers, app designers, end users, and healthcare professionals in designing, evaluating, recommending and adopting mHealth applications.

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Section: Iv1 Study Selection and Data Extractionmentioning

confidence: 99%

Security and Privacy of mHealth Applications: A Scoping Review

2020

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“…An approach often taken is to analyse motifs in the graph to extract high-level abstractions (e.g., Missier et al [20]), meaningful to the average end-user. In recent work [26], it was proposed to represent such a high-level abstractions as a comic strip.…”

Section: How To Communicate Information?mentioning

confidence: 99%

Personal data and the internet of things

2019

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The Internet of Things promises a connected environment reacting to and addressing our every need, but based on the assumption that all of our movements and words can be recorded and analysed to achieve this end. Ubiquitous surveillance is also a precondition for most dystopian societies, both real and fictional. How our personal data is processed and consumed in an ever more connected world must imperatively be made transparent, and more effective technical solutions than those currently on offer, to manage personal data must urgently be investigated.

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“…More important at this stage, is that data flow capture is built into apps to support user-inspection interfaces. We are already seeing alternative representations in research [43]; one interesting approach uses 'comic strip' visualisation techniques to communicate the logic of automated processing to end users [44].…”

Section: Features Enabling Gdpr Compliancementioning

confidence: 99%

Developing GDPR Compliant Apps for the Edge

Lodge

Crabtree

Brown

2018

Lecture Notes in Computer Science

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We present an overview of the Databox application development environment or SDK as a means of enabling trusted IoT app development at the network edge. The Databox platform is a dedicated domestic platform that stores IoT, mobile and cloud data and executes local data processing by third party apps to provide end-user control over data flow. Key challenges for building apps in edge environments concern (i) the complexity of IoT devices and user requirements, and (ii) supporting privacy preserving features that meet new data protection regulations. We examine how the Databox SDK can ease the burden of regulatory compliance and be used to sensitize developers to privacy related issues in the very course of building apps.

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Tracing Personal Data Using Comics

Cited by 7 publications

References 17 publications

Security and Privacy of mHealth Applications: A Scoping Review

Security and Privacy of mHealth Applications: A Scoping Review

Personal data and the internet of things

Developing GDPR Compliant Apps for the Edge

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