Abstract
The volume of data generated worldwide is rapidly growing. Cloud computing, fog computing, and the Internet of things (IoT) technologies have been adapted to compute and process this high data volume. In coming years information technology will enable extensive developments in the field of healthcare and offer health care providers and patients broadened opportunities to enhance their healthcare experiences and services owing to heightened availability and enriched services through real-time data exchange. As promising as these technological innovations are, security issues such as data integrity and data consistency remain widely unaddressed. Therefore, it is important to engineer a solution to these issues. Developing a damage assessment and recovery control model for fog computing is critical. This paper proposes two models for using fog computing in healthcare: one for private fog computing distribution and one for public fog computing distribution. For each model, we propose a unique scheme to assess the damage caused by malicious attack, to accurately identify affected transactions and recover damaged data if needed. A transaction-dependency graph technique is used for both models to observe and monitor all transactions in the whole system. We conducted a simulation study to assess the applicability and efficacy of the proposed models. The evaluation rendered these models practicable and effective.
Highlights
Fog computing has been widely applied in the healthcare industry, which has attracted the attention of numerous researchers [17,18]
Fog computing emerged as a solution to the issues manifest in the cloud computing paradigm
Fog computing has been used successfully for smart system data management; fog computing is vulnerable to attackers capable of injecting malicious transactions into a fog node’s database
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. As a solution to cloud computing performance related issues, e.g., high response time and real time data processing [1], CISCO introduced fog computing in 2012 , as multiple clouds are deployed close to the ground. We proposed two models to protect against data integrity violation by assessing damage and performing data recovery in case an attack has targeted a fog node(s). We proposed a new model where we consider the case that the health organization has only public fog nodes which makes it impossible to have a trusted fog node.
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