Exploring the usability, security and privacy taxonomy for mobile health applications

Asaddok, Norhidayah; Ghazali, Masitah

doi:10.1109/icriis.2017.8002472

Cited by 12 publications

(13 citation statements)

References 27 publications

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“…Granularity designates the data transfer required for the type of access and purpose for that particular request. The work of Asaddok et al [11] involves mobile devices in the area of health (Mobile Health (mHealth) and the parameters: usability, security, and privacy. The authors propose a taxonomy that involves the three parameters mentioned, and, for each, it branches into taxonomies.…”

Section: Related Workmentioning

confidence: 99%

“…Asaddok and Ghazali [11] defined data access based on access to patient identity information, personal health information, and personal health records, moreover defined in their taxonomy as identity, access, and disclosure. Coen-Porisini et al [12] say that data access must be based on access control based on the users and their roles.…”

Section: Related Workmentioning

confidence: 99%

“…The authors describe potential attacks for these devices, as side-channel, tag cloning, tampering devices, and sensor tracking. In the work of Asaddok and Ghazali [11], the authors classified mobile devices as part of the application dimension of the taxonomy, present in the topic 'patient care and monitoring', as they are used for observation of the patient.…”

Section: Related Workmentioning

confidence: 99%

“…Granularity is focused on the characteristics of that data to direct it to the appropriate use and a dimension that deals with the data's purpose. In the work of Asaddok and Ghazali [11], the authors developed a taxonomy containing usability, security, and privacy aspects to mHealth applications. Each item of the taxonomy is derived in three or more sub-items.…”

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

Lucca

Silva

Luchtenberg

et al. 2020

Sensors

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Data on diagnosis of infection in the general population are strategic for different applications in the public and private spheres. Among them, the data related to symptoms and people displacement stand out, mainly considering highly contagious diseases. This data is sensitive and requires data privacy initiatives to enable its large-scale use. The search for population-monitoring strategies aims at social tracking, supporting the surveillance of contagions to respond to the confrontation with COVID-19. There are several data privacy issues in environments where IoT devices are used for monitoring hospital processes. In this research, we compare works related to the subject of privacy in the health area. To this end, this research proposes a taxonomy to support the requirements necessary to control patient data privacy in a hospital environment. According to the tests and comparisons made between the variables compared, the application obtained results that contribute to the scenarios applied. In this sense, we modeled and implemented an application. By the end, a mobile application was developed to analyze the privacy and security constraints with COVID-19.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

Lucca

Silva

Luchtenberg

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Also, these attacks can influence privacy attributes i.e. privacy identity, privacy access, and privacy disclosure [20]. From a security perspective, confidentiality is one of the security attributes associated with securing and privately controlled the users' data.…”

Section: Introductionmentioning

confidence: 99%

User Privacy and Data Flow Control for Android Apps: Systematic Literature Review

Al-Kindi

Sarrab

Alzeidi

2021

JCSANDM

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Android mobile apps gain access to numerous users’ private data. Users of different Android mobile apps have less control over their sensitive data during their installation and run-time. Too often, these apps consider data privacy less serious than users’ expectations. Many mobile apps misbehave and upload users’ data without permission which confirmed the possibility of privacy leakage through different network channels. The literature has proposed various approaches to protect user’s data and avoid privacy violations. In this paper, we provide a comprehensive overview of state-of-art research on Android user privacy, and data flow control. the aim is to highlight the main trends, pinpoint the main methodologies applied, and enumerate the privacy violations faced by Android users. We also shed some light on the directions where the researcher’s community effort is still needed. To this end, we conduct a Systematic Literature Review (SLR) during which we surveyed 114 relevant research papers published in leading conferences and journals. Our thorough examination of the relevant literature has led to a critical analysis of the proposed solutions with a focus on user privacy extensions and mechanism for the Android mobile platform. Furthermore, possible solutions and research directions have been discussed.

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Design Considerations of Mobile Applications for Healthy Living

Değerli

2023

Studies in Big Data

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Exploring the usability, security and privacy taxonomy for mobile health applications

Cited by 12 publications

References 27 publications

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

User Privacy and Data Flow Control for Android Apps: Systematic Literature Review

Design Considerations of Mobile Applications for Healthy Living

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