Research Article Volume 5 Issue 8

Preserving Privacy in Fog Computing: Exploring Emerging Technologies and Best Practices

Sepideh Sarayloo* and Mahtab Iltarabian

Faculty of Engineering, Islamic Azad University, North Tehran Branch, Iran

*Corresponding Author: Sepideh Sarayloo, Faculty of Engineering, Islamic Azad University, North Tehran Branch, Iran.

Received: July 04, 2023; Published: July 25, 2023


This article explores the crucial topic of privacy preservation in fog computing—an emerging paradigm that brings computation and data storage closer to the network edge. Fog computing offers numerous advantages, but it also presents unique challenges in maintaining privacy in distributed environments. The article delves into the intersection of privacy and fog computing, examining emerging technologies and trends that contribute to privacy preservation. It covers areas such as artificial intelligence (AI) and machine learning (ML) for privacy-aware processing, the impact of blockchain and distributed ledger technology (DLT), and the role of other emerging technologies in preserving privacy. Case studies, success stories, challenges, and future directions are discussed to provide real-world context and insights. The article concludes with practical recommendations for adhering to privacy regulations, designing privacy-aware architectures, and fostering user awareness and control. By addressing these key aspects, the article equips readers with a comprehensive understanding of privacy preservation in fog computing and offers guidance for building robust and privacy-conscious fog computing applications.

Keywords: Privacy Preservation; Fog Computing; Emerging Technologies; AI and ML; Privacy Regulations; Data Protection; Edge Computing


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Citation: Sepideh Sarayloo and Mahtab Iltarabian. “Preserving Privacy in Fog Computing: Exploring Emerging Technologies and Best Practices".Acta Scientific Computer Sciences 5.8 (2023): 26-38.


Copyright: © 2023 Sepideh Sarayloo and Mahtab Iltarabian. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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