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


  1. Kinza Sarwar., et al. “Lightweight, Divide-and-Conquer privacy-preserving data aggregation in fog computing”. Future Generation Computer Systems 119 (2021): 188-199.
  2. Kinza Sarwar., et al. “A Survey on Privacy Preservation in Fog-Enabled Internet of Things”. ACM Computing Surveys 1 (2023): 39.
  3. Kumar J and Singh AK. “Security and Privacy-Preservation of IoT Data in Cloud-Fog Computing Environment”. ArXiv (2022).
  4. N Abubaker., et al. “Privacy-preserving fog computing paradigm”. 2017 IEEE Conference on Communications and Network Security (CNS), Las Vegas, NV, USA (2017): 502-509.
  5. Jasleen Kaur., et al. “Encryfuscation: A model for preserving data and location privacy in fog based IoT scenario”. Journal of King Saud University - Computer and Information Sciences9 (2022): 6808-6817.
  6. Bindu Madavi KP and Vijayakarthick P. “Decoy Technique for Preserving the Privacy in Fog Computing”. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies. Springer, Singapore 53 (2020).
  7. Yildirim Okay F., et al. “Fog computing-based privacy preserving data aggregation protocols”. Transactions on Emerging Telecommunications Technologies 31 (2020): e3900.
  8. Chunhui Piao., et al. “Privacy-preserving governmental data publishing: A fog-computing-based differential privacy approach”. Future Generation Computer Systems 90 (2019): 158-174.
  9. Rana S., et al. “Privacy-Preserving Key Agreement Protocol for Fog Computing Supported Internet of Things Environment”. Wireless Personal Communications 119 (2021): 727-747.
  10. Security and Privacy in Fog Computing: Challenges (
  11. Y Guan., et al. “Data Security and Privacy in Fog Computing". in IEEE Network 32.5 (2018): 106-111.
  12. Khalid Tauqeer., et al. “A survey on privacy and access control schemes in fog computing”. International Journal of Communication Systems 34 (2021).
  13. M Mukherjee., et al. “Security and Privacy in Fog Computing: Challenges". in IEEE Access 5 (2017): 19293-19304.
  14. F Pallas., et al. “Fog Computing as Privacy Enabler”. in IEEE Internet Computing 24.4 (2020): 15-21.
  15. Yildirim Okay F., et al. “Fog computing-based privacy preserving data aggregation protocols”. Transactions on Emerging Telecommunications Technologies 31 (2020): e3900.
  16. Farhadi M., et al. “A systematic approach toward security in Fog computing: Assets, vulnerabilities, possible countermeasures”. Software: Practice and Experience 50 (2020): 973-997.
  17. Alwakeel AM. “An Overview of Fog Computing and Edge Computing Security and Privacy Issues”. Sensors (Basel)24 (2021): 8226.
  18. Khan S., et al. “Fog computing security: a review of current applications and security solutions”. Journal of Cloud Computing 6 (2017): 19.
  19. Witti Moussa., et al. “Secure and Privacy-aware Data Collection Architecture Approach in Fog Node Based Distributed IoT Environment”. 19-32.
  20. Benhamida FZ., et al. “PyFF: A Fog-Based Flexible Architecture for Enabling Privacy-by-Design IoT-Based Communal Smart Environments”. Sensors (Basel)11 (2021): 3640.
  21. Sabrina Sicari., et al. “Insights into security and privacy towards fog computing evolution”. Computers and Security 120 (2022): 102822.
  22. Connected IoT Devices Forecast. Help Net Security 2019 [cited 2019; 41.6 billion IoT devices will be generating 79.4 zettabytes of data in 2025] (2019).
  23. Xin Li., et al. “Privacy information verification of homomorphic algorithm for aggregated data based on fog layer structure”. Computer Communications 181 (2022): 309-319.
  24. Deebak BD and AL-Turjman Fadi. “Privacy-preserving in smart contracts using blockchain and artificial intelligence for cyber risk measurements”. Journal of Information Security and Applications 58 (2021): 102749.
  25. X`F Ghedira-Guegan., et al. “Privacy-Preserving IoT Data Aggregation Based on Blockchain and Homomorphic Encryption”. Sensors (Basel)7 (2021): 2452.
  26. Hameed Karrar., et al. “A Review of Fog Computing and Machine Learning: Concepts, Applications, Challenges, and Open Issues”. IEEE Access (2019).
  27. Zhao Ruoli., et al. “ePMLF: Efficient and Privacy-Preserving Machine Learning Framework Based on Fog Computing”. International Journal of Intelligent Systems (2023): 1-16.
  29. Roy C., et al. “A fog computing-based IoT framework for prediction of crop disease using big data analytics”. AI, Edge and IoT-based Smart Agriculture (2022): 287-300.
  30. Ashi Zain., et al. “Fog computing: security challenges and countermeasures”. International Journal of Computer Applications 175 (2020): 30-36.
  31. R Shahzadi., et al. “Three tier fog networks: Enabling IoT/5G for latency sensitive applications”. in China Communications 16.3 (2019): 1-11.
  32. Muneeb M., et al. “A Fog Computing Architecture with Multi-Layer for Computing-Intensive IoT Applications”. Applied Science 11 (2021): 11585.


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.


Acceptance rate35%
Acceptance to publication20-30 days

Indexed In

News and Events

  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is July 30, 2024.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of "Best Article of the Issue"
  • Welcoming Article Submission
    Acta Scientific delightfully welcomes active researchers for submission of articles towards the upcoming issue of respective journals.

Contact US