Secure Fog-Cloud of Things

Alli, Adam A.; Kalinaki, Kassim; Nambobi, Mutwalibi; Hamid, Habiba; Ibrahim, Lwembawo

doi:10.1201/9781003028635-2

Cited by 10 publications

(2 citation statements)

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“…On the other hand, privacy is defined as protecting sensitive information from unauthorized disclosure, such as PII included with medical data. Further privacy is mainly focused on developing appropriate policies and authentication and authorization procedures towards guaranteeing that patient private data are collected, shared, and used appropriately [20][21][22][23]45].…”

Section: Data Consumption and Sharingmentioning

confidence: 99%

“…Real-time security analytics Because of the increasing threats, analyzing security and privacy threats and forecasting threat sources in real-time is critical in the healthcare industry. The healthcare business is currently dealing with a slew of sophisticated threats, including ransomware, Distributed Denial of Service (DDoS), and all sorts of malware [10,13,45]. Furthermore, social engineering attacks are becoming more common, and the hazards associated with them are difficult to forecast without taking human cognitive behavior into account.…”

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confidence: 99%

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A Novel Cloud Enabled Access Control Model for Preserving the Security and Privacy of Medical Big Data

2023

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In the context of healthcare, big data refers to a complex compilation of digital medical data collected from many sources that are difficult to manage with normal technology and software due to its size and complexity. These big data are useful in various aspects of healthcare, such as disease diagnosis, early prevention of diseases, and predicting epidemics. Even though medical big data has many advantages and a lot of potential for revolutionizing healthcare, it also has a lot of drawbacks and problems, of which security and privacy are of the utmost concern, owing to the severity of the complications once the medical data is compromised. On the other hand, it is evident that existing security and privacy safeguards in healthcare organizations are insufficient to protect their massive, big data repositories and ubiquitous environment. Thus, motivated by the synthesizing of the current knowledge pertaining to the security and privacy of medical big data, including the countermeasures, in the study, firstly, we provide a comprehensive review of the security and privacy of medical big data, including countermeasures. Secondly, we propose a novel cloud-enabled hybrid access control framework for securing the medical big data in healthcare organizations, and the result of this research indicates that the proposed access control model can withstand most cyber-attacks, and it is also proven that the proposed framework can be utilized as a primary base to build secure and safe medical big data solutions. Thus, we believe this research would be useful for future researchers to comprehend the knowledge on the security and privacy of medical big data and the development of countermeasures.

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