Exploring the need for a suitable privacy framework for mHealth when managing chronic diseases

Jusob, Farad Rafique; George, Carlisle; Mapp, Glenford

doi:10.1007/s40860-017-0049-7

Cited by 11 publications

(20 citation statements)

References 26 publications

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“…Therefore, the implementation of mHealth devices and applications has great significance and has risen to the national strategy of China [ 49 ]. However, privacy violation has become one of the most serious obstacles to the implementation of mHealth [ 50 , 51 ].…”

Section: Evolutionary Game Model Of Privacy Investmentmentioning

confidence: 99%

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

Zhu

Liu

Feng

2018

IJERPH

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With the rapid deployment of mobile technologies and their applications in the healthcare domain, privacy concerns have emerged as one of the most critical issues. Traditional technical and organizational approaches used to address privacy issues ignore economic factors, which are increasingly important in the investment strategy of those responsible for ensuring privacy protection. Taking the mHealth system as the context, this article builds an evolutionary game to model three types of entities (including system providers, hospitals and governments) under the conditions of incomplete information and bounded rationality. Given that the various participating entities are often unable to accurately estimate their own profits or costs, we propose a quantified approach to analyzing the optimal strategy of privacy investment and regulation. Numerical examples are provided for illustration and simulation purpose. Based upon these examples, several countermeasures and suggestions for privacy protection are proposed. Our analytical results show that governmental regulation and auditing has a significant impact on the strategic choice of the other two entities involved. In addition, the strategic choices of system providers and hospitals are not only correlated with profits and investment costs, but they are also significantly affected by free riding. If the profit growth coefficients increase to a critical level, mHealth system providers and hospitals will invest in privacy protection even without the imposition of regulations. However, the critical level is dependent on the values of the parameters (variables) in each case of investment and profits.

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Section: Evolutionary Game Model Of Privacy Investmentmentioning

confidence: 99%

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

Zhu

Liu

Feng

2018

IJERPH

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“…The authors conducted a previous study comparing relevant existing regulatory frameworks for privacy and how they address privacy concerns in mHealth (Jusob et al 2017 ). These frameworks included: Health Privacy Project (HPP) Best Practice Principles of 2007 (Kotz et al 2009 ); Markle Common Framework of 2008 (Markle Foundation 2008 ); Office of the National Coordinator for Health Information Technology (ONC) Nationwide Privacy and Security Framework for Electronic Exchange of Individually Identifiable Health Information of 2008 (ONC 2008 ); Generally Accepted Privacy Principles (GAPP) of 2008 (Prosch 2008 ); A Privacy Framework for Mobile Health and Home-Care Systems (MHHCS) of 2009 (Kotz et al 2009 ); Organisation for Economic Co-operation and Development (OECD) Principles of 2013 (OECD 2013 ); General Data Protection Regulation (GDPR) (EC 2016 ).…”

Section: Comparison Of Relevant Existing Regulatory Framework For Privacymentioning

confidence: 99%

A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world

Jusob

George

Mapp

2021

J Public Health (Berl.)

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Aim New challenges are being faced by global healthcare systems such as an increase in the elderly population, budget cuts as well as the ongoing Covid-19 pandemic. As pressures mount on healthcare systems to provide treatment to patients, mHealth is seen as one of the possible solutions to addressing these challenges. Given the sensitivity of health data, the rapid development of the mHealth sector raises privacy concerns. The aims of this research were to investigate privacy threats/concerns in the context of mHealth and the management of chronic diseases and to propose a novel privacy framework to address these concerns. Subject and method The study adopted a modified version of the engineering design process. After defining the problem, information was gathered through literature reviews, and analyses of existing regulatory (privacy) frameworks and past research on privacy threats/concerns. Requirements for a new framework were then specified leading to its development and comparison with existing frameworks. Results A novel future-proof privacy framework was developed and illustrated. Using existing regulatory frameworks for privacy and privacy threats/concerns from research studies, privacy principles and their resulting requirements were identified. Furthermore, mechanisms and associated technologies needed to implement the privacy principles/requirements into a functional prototype were also identified. A comparison of the proposed framework with existing frameworks, showed that it addressed privacy threats/concerns in a more comprehensive manner. Conclusion This research makes a valuable contribution to protecting privacy in mHealth. The novel framework developed is an improvement on existing frameworks. It is also future-proof since its foundations are built on regulatory frameworks and privacy threats/concerns existing at the time of its deployment/revision.

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“…9 3. HPP Best Principles [46][47][48] 2. HPP Best Principles [46][47][48] Employers should present Personal health record that is transferable, to the degree practical, enabling representatives to keep up or move the PHR as well as the information it contains even after employment or scope finishes or changes.…”

Section: Health Privacy Project (Hpp) Best Practicesmentioning

confidence: 99%

“…47,50 4. HPP Best Practices 43,46 The reasons for which individual information is gathered should be specified at the time of accumulation, and ensuing the use should be constrained to those reasons, or others that are specified on each event of the progress of reason.…”

Section: Markle: Common Frameworkmentioning

confidence: 99%

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A multivariant secure framework for smart mobile health application

Butt

Jamal

Azad

et al. 2019

Trans Emerging Tel Tech

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Wireless sensor network enables remote connectivity of technological devices such as smart mobile with the internet. Due to its low cost as well as easy availability of data sharing and accessing devices, the Internet of Things (IoT) has grown exponentially during the past few years. The availability of these devices plays a remarkable role in the new era of mHealth. In mHealth, the sensors generate enormous amounts of data and the context-aware computing has proven to collect and manage the data. The context aware computing is a new domain to be aware of context of involved devices. The context-aware computing is playing a very significant part in the development of smart mobile health applications to monitor the health of patients more efficiently. Security is one of the key challenges in IoT-based mHealth application development. The wireless nature of IoT devices motivates attackers to attack on application; these vulnerable attacks can be denial of service attack, sinkhole attack, and select forwarding attack. These attacks lead intruders to disrupt the application's functionality, data packet drops to malicious end and changes the route of data and forwards the data packet to other location. There is a need to timely detect and prevent these threats in mobile health applications. Existing work includes many security frameworks to secure the mobile health applications but all have some drawbacks. This paper presents existing frameworks, the impact of threats on applications, on information, and different security levels. From this line of research, we propose a security framework with two algorithms, ie, (i) patient priority autonomous call and (ii) location distance based switch, for mobile health applications and make a comparative analysis of the proposed framework with the existing ones.

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Exploring the need for a suitable privacy framework for mHealth when managing chronic diseases

Cited by 11 publications

References 26 publications

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

An Evolutionary Game-Theoretic Approach for Assessing Privacy Protection in mHealth Systems

A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world

A multivariant secure framework for smart mobile health application

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