Designing a secure architecture for m-health applications

Alibasa, Muhammad Johan; Santos, Marlon R.; Glozier, Nick; Harvey, Samuel B.; Calvo, Rafael A.

doi:10.1109/lsc.2017.8268151

Cited by 9 publications

(10 citation statements)

References 17 publications

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“…These security risks pose a significant barrier to the adoption of 5G-enabled healthcare services. Inability to protect the privacy and security of patient data has both social and economic consequences (Burns & Johnson, 2015;Alibasa et al, 2017). For example, a breach in the integrity of patient data can result in misdiagnosis, mistreatment and possibly death.…”

Section: Latencymentioning

confidence: 99%

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Security architecture for a 5G mHealth system

Malila

Mutsvangwa

2019

GHI

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Global health challenges and the proliferation of mobile technologies have been key in the adoption of mHealth for provision of low-cost and equitable healthcare. Evolution of mobile networks to 5G is expected to revolutionise healthcare service delivery due to the stringent performance requirements imposed on 5G. However, because of the open nature of 5G systems, securing patient health information has been identified as a significant barrier to the full adoption of mHealth. In this paper, we propose a security architecture for an mHealth system based on a review of standard principles and guidelines for designing 5G security systems. We present a structured approach for developing and implementing an end-to-end 5G mHealth security system. We propose a security architecture that can be realised using keyless signature infrastructure Blockchain and X-tee technology to secure the communication system including hospital and third-party health data networks, physical layer security for securing the wireless interface in access networks, physical unclonable functions, and a trusted execution environment for securing end-user devices. We propose the adoption of network slicing for isolating health systems from other 5G industry verticals. We define system domains that are used to identify security threats and propose mechanisms to mitigate these threats.

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Section: Latencymentioning

confidence: 99%

“…However, they do not provide end-to-end security guarantees for health data. Alibasa et al (2017) proposed a security architecture that focuses on the data storage network domain. The architecture separately stores identifiable and non-identifiable patient data on servers.…”

Section: Security Architecturesmentioning

confidence: 99%

Security architecture for a 5G mHealth system

Malila

Mutsvangwa

2019

GHI

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“…[5], [6] Availability Clinical data must be easily accessible to authorized people, whenever they require it.…”

Section: Integritymentioning

confidence: 99%

“…[5], [6] Digital Object Identifier (DOI): http://dx.doi.org/10.18687/LACCEI2019. Access Control Doctors, nurses and patients access the information previously shared by the data owner.…”

Section: Integritymentioning

confidence: 99%

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Security model to protect patient data in mHealth systems through a Blockchain network

Díaz¹,

Armas²,

Molina³

et al. 2019

Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: “Industry, Innovation

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On this research paper we propose a security model to protect patient data on mobile health systems (mHealth) through a Blockchain network. This model is implemented under a Blockchain platform that allows collecting, sharing and integrating data in a safe way through a mobile app for mHealth devices, for medical care in Peruvian clinics. This security model consists of three stages: 1. Data collection, 2. Data processing, 3. System monitoring. It should be noted that the patient is autonomous in the management of his information, and that each user requires a single identifier to get access to the data. A test scenario was defined to validate the proposed model. Also, the study was conducted with a group of users through a health mobile app and the used medical data was provided by a hospital in Peru as anonymized research data. During the study, we validated the following topics: access control to the network, access to medical information of authorized users, data integrity on each transaction and performance evaluation of the system under a high user transaction load. Preliminary results show the system average response time is 4.72 seconds for 10,000 users carrying out requests simultaneously.

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Supporting Mood Introspection from Digital Footprints

Alibasa

Calvo

2019

2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)

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Designing a secure architecture for m-health applications

Cited by 9 publications

References 17 publications

Security architecture for a 5G mHealth system

Security architecture for a 5G mHealth system

Security model to protect patient data in mHealth systems through a Blockchain network

Supporting Mood Introspection from Digital Footprints

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