
Full text loading...
We use cookies to track usage and preferences.I Understand
Privacy plays a substantial role in both public and private, databases especially in the healthcare industry and government sectors require a high-confidential data transmission process. Most often, these data contain personal information that must be concealed throughout data processing and transmission between terminal devices and cloud data centers, such as username, ID, account information, and a few more sensitive details. Recently, fog computing highly utilized for such data transmission, storing, and network interconnection processes due to its low latency, mobility, reduced computational cost, position awareness, data localization, and geographical distribution. It delivers to cloud computing and the widespread positioning of IoT applications. Since fog-based service is provided to the massive-scale end-end users by fog server/node, privacy is a foremost concern for fog computing. Fog computing poses several challenges if it comes to delivering protected data transfer; making the development of privacy preservation strategies particularly desirable. This paper exhibits a systematical literature review (SLR) on privacy preservation methods developed for fog computing in terms of issues, challenges, and various solutions. The main objective of this paper is to categorize the existing privacy-related research methods and solutions that have been published between 2012 and 2022 using analytical and statistical methods. The next step is to present specific practical issues in this area. Depending on the issues, the merits and drawbacks of each suggested fog security method are explored, and some suggestions are made for how to tackle the privacy concerns with fog computing. To build, deploy, and maintain fog systems, several imminent motivational directions and open concerns in this topic were presented.
Article metrics loading...
Full text loading...
References
Data & Media loading...