Data Risks Identification in Healthcare Sensor Networks

Lopatina, Kate; Dokuchaev, V. A.; Maklachkova, V. V.

doi:10.1109/emctech53459.2021.9619178

Cited by 5 publications

(1 citation statement)

References 10 publications

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“… [S15]Threat Modelling for Mobile Health Systems [ 92 ] Threat modelling for mHealth using STRIDE and DREAD. [S16] Data Risks Identification in Healthcare Sensor Networks [ 137 ] Risk assessment for HIoT showing risks and countermeasures. [S17] Data Protection and Privacy of the Internet of Healthcare Things (IoHTs) [ 29 ] A review study covering Privacy by design for HIoT and privacy assessment recommendations.…”

Section: Table A1mentioning

confidence: 99%

Cybersecurity Risk Management Framework for Blockchain Identity Management Systems in Health IoT

Alamri

Crowley

Richardson

2022

Sensors

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Blockchain (BC) has recently paved the way for developing Decentralized Identity Management (IdM) systems for different information systems. Researchers widely use it to develop decentralized IdM systems for the Health Internet of Things (HIoT). HIoT is considered a vulnerable system that produces and processes sensitive data. BC-based IdM systems have the potential to be more secure and privacy-aware than centralized IdM systems. However, many studies have shown potential security risks to using BC. A Systematic Literature Review (SLR) conducted by the authors on BC-based IdM systems in HIoT systems showed a lack of comprehensive security and risk management frameworks for BC-based IdM systems in HIoT. Conducting a further SLR focusing on risk management and supplemented by Grey Literature (GL), in this paper, a security taxonomy, security framework, and cybersecurity risk management framework for the HIoT BC-IdM systems are identified and proposed. The cybersecurity risk management framework will significantly assist developers, researchers, and organizations in developing a secure BC-based IdM to ensure HIoT users’ data privacy and security.

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