A Taxonomic Perspective on Certification Schemes: Development of a Taxonomy for Cloud Service Certification Criteria
Proceedings of the 47th Hawaii International Conference on System Sciences (HICSS 2014), 2014
Numerous cloud service certifications (CSCs) are emerging in practice. However, in their striving... more Numerous cloud service certifications (CSCs) are emerging in practice. However, in their striving to establish the market standard, CSC initiatives proceed independently, resulting in a disparate collection of CSCs that are predominantly proprietary, based on various standards, and differ in terms of scope, audit process, and underlying certification schemes. Although literature suggests that a certification’s design influences its effectiveness, research on CSC design is lacking and there are no commonly agreed structural characteristics of CSCs. Informed by data from 13 expert interviews and 7 cloud computing standards, this paper delineates and structures CSC knowledge by developing a taxonomy for criteria to be assessed in a CSC. The taxonomy consists of 6 dimensions with 28 subordinate characteristics and classifies 328 criteria, thereby building foundations for future research to systematically develop and investigate the efficacy of CSC designs as well as providing a knowledge base for certifiers, cloud providers, and users.
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Papers by Fangjian Gao
Objective: The objective of this study was to establish an overview of mHealth apps offered on iOS and Android with a special focus on potential damage to users through information security and privacy infringements.
Methods: We assessed apps available in English and offered in the categories “Medical” and “Health & Fitness” in the iOS and Android App Stores. Based on the information retrievable from the app stores, we established an overview of available mHealth apps, tagged apps to make offered information machine-readable, and clustered the discovered apps to identify and group similar apps. Subsequently, information security and privacy implications were assessed based on health specificity of information available to apps, potential damage through information leaks, potential damage through information manipulation, potential damage through information loss, and potential value of information to third parties.
Results: We discovered 24,405 health-related apps (iOS; 21,953; Android; 2452). Absence or scarceness of ratings for 81.36% (17,860/21,953) of iOS and 76.14% (1867/2452) of Android apps indicates that less than a quarter of mHealth apps are in more or less widespread use. Clustering resulted in 245 distinct clusters, which were consolidated into 12 app archetypes grouping clusters with similar assessments of potential damage through information security and privacy infringements. There were 6426 apps that were excluded during clustering. The majority of apps (95.63%, 17,193/17,979; of apps) pose at least some potential damage through information security and privacy infringements. There were 11.67% (2098/17,979) of apps that scored the highest assessments of potential damages.
Conclusions: Various kinds of mHealth apps collect and offer critical, sensitive, private medical information, calling for a special focus on information security and privacy of mHealth apps. In order to foster user acceptance and trust, appropriate security measures and processes need to be devised and employed so that users can benefit from seamlessly accessible, tailored mHealth apps without exposing themselves to the serious repercussions of information security and privacy infringements.
Objective: The objective of this study was to establish an overview of mHealth apps offered on iOS and Android with a special focus on potential damage to users through information security and privacy infringements.
Methods: We assessed apps available in English and offered in the categories “Medical” and “Health & Fitness” in the iOS and Android App Stores. Based on the information retrievable from the app stores, we established an overview of available mHealth apps, tagged apps to make offered information machine-readable, and clustered the discovered apps to identify and group similar apps. Subsequently, information security and privacy implications were assessed based on health specificity of information available to apps, potential damage through information leaks, potential damage through information manipulation, potential damage through information loss, and potential value of information to third parties.
Results: We discovered 24,405 health-related apps (iOS; 21,953; Android; 2452). Absence or scarceness of ratings for 81.36% (17,860/21,953) of iOS and 76.14% (1867/2452) of Android apps indicates that less than a quarter of mHealth apps are in more or less widespread use. Clustering resulted in 245 distinct clusters, which were consolidated into 12 app archetypes grouping clusters with similar assessments of potential damage through information security and privacy infringements. There were 6426 apps that were excluded during clustering. The majority of apps (95.63%, 17,193/17,979; of apps) pose at least some potential damage through information security and privacy infringements. There were 11.67% (2098/17,979) of apps that scored the highest assessments of potential damages.
Conclusions: Various kinds of mHealth apps collect and offer critical, sensitive, private medical information, calling for a special focus on information security and privacy of mHealth apps. In order to foster user acceptance and trust, appropriate security measures and processes need to be devised and employed so that users can benefit from seamlessly accessible, tailored mHealth apps without exposing themselves to the serious repercussions of information security and privacy infringements.