Skip to main content

A Systematic Survey on Security Challenges for Fog-Enabled Internet of Things (IoT) and Industrial Internet of Things (IIoT)

  • Chapter
  • First Online:
Security Issues in Fog Computing from 5G to 6G

Part of the book series: Internet of Things ((ITTCC))

Abstract

In recent years, fog computing is the extended technology of cloud computing platforms by providing the services and resources on the edge of the enterprise’s network and integrated with the Internet of Things (IoT) and Industrial Internet of Things (IIoT). Internet of Things is considered as a smart objects scheme, which furnishes the sensors, processing devices and network technologies together to build an ecosystem to deliver smart services to the end users. These applications can be utilized for enhancing the production of the goods and mitigating the risk of disaster occurrences in industries, which is known as the Industrial Internet of Things (IIoT), or Industry 4.0. This new paradigm provides many benefits to the industries, but it also introduces serious security challenges. The device heterogeneity, integrity and configuration expose the industrial infrastructure to potential threats, such as man-in-the-middle, black hole, wormhole, malicious configuration attacks and inherited security and privacy challenges from cloud computing in the fog-enabled platform. In this chapter, we intend to thoroughly discuss fog-enabled architecture Internet of Things and Industrial Internet of Things where computing, storage services and deployment are on the edge of the network to provide better services to users. This chapter aims to systematically and statistically classify and analyse various security challenges and attacks addressed by various researchers for the fog-enabled IoT and IIoT environment. When two or more heterogeneous devices communicate and share information, ‘trust’ plays a significant role. So, the authors have considered the ‘trust’ in this study and examined various security issues. Moreover, it is studied and emphasized on zero trust security model importance and requirements for fog-enabled IoT and IIoT environments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lampropoulos, G., et al. (2019). Internet of things in the context of Industry 4.0: An overview. Sciendo-International Journal of Entrepreneurial Knowledge, 7(2), 4–19.

    Article  Google Scholar 

  2. Statista Research Department. (2021). Number of internet of things (IoT) connected devices worldwide in 2018, 2025 and 2030. Accessed 27 February, 2021. https://www.statista.com/statistics/802690/worldwide-connected-devices-by-access-technology/

  3. Aleisa, M. A., Abuhussein, A., & Sheldon, F. T. (2020). Access control in fog computing: Challenges and research agenda. IEEE Access, 8, 83986–83999.

    Article  Google Scholar 

  4. Stolfo, S. J., Salem, M. B., & Keromytis, A. D. (2012). Fog computing: Mitigating insider data theft attacks in the cloud. In 2012 IEEE symposium on security and privacy workshops. IEEE.

    Google Scholar 

  5. Sriram, M., et al. (2014). A hybrid protocol to secure the cloud from insider threats. In 2014 IEEE international conference on cloud computing in emerging markets (CCEM). IEEE.

    Google Scholar 

  6. Li, Z., et al. (2017). A non-cooperative differential game-based security model in fog computing. China Communications, 14(1), 180–189.

    Article  Google Scholar 

  7. Butun, I., Sari, A., & Österberg, P. (2019). Security implications of fog computing on the internet of things. In 2019 IEEE international conference on consumer electronics (ICCE). IEEE.

    Google Scholar 

  8. Diro, A. A., & Chilamkurti, N. (2018). Distributed attack detection scheme using deep learning approach for Internet of Things. Future Generation Computer Systems, 82, 761–768.

    Article  Google Scholar 

  9. Sohal, A. S., et al. (2018). A cybersecurity framework to identify malicious edge device in fog computing and cloud-of-things environments. Computers & Security, 74, 340–354.

    Article  Google Scholar 

  10. Wang, T., et al. (2018). Fog-based storage technology to fight with cyber threat. Future Generation Computer Systems, 83, 208–218.

    Article  Google Scholar 

  11. Shankarwar, M. U., & Pawar, A. V. (2015). Security and privacy in cloud computing: A survey. In Proceedings of the 3rd international conference on Frontiers of intelligent computing: Theory and applications (FICTA) 2014. Springer.

    Google Scholar 

  12. Khan, N. S., Chishti, M. A., & Saleem, M. (2019). Identifying various risks in cyber-security and providing a mind-map of network security issues to mitigate cyber-crimes. In Proceedings of 2 nd International conference on communication, computing and networking. Springer.

    Google Scholar 

  13. Maimó, L. F., et al. (2018). Dynamic management of a deep learning-based anomaly detection system for 5G networks. Journal of Ambient Intelligence and Humanized Computing, 10(8), 3083–3097.

    Article  Google Scholar 

  14. Gandhi, U. D., et al. (2018). HIoTPOT: Surveillance on IoT devices against recent threats. Wireless Personal Communications, 103(2), 1179–1194.

    Article  Google Scholar 

  15. Ziegeldorf, J. H., Morchon, O. G., & KlausWehrle. (2014). Privacy in the internet of things: Threats and challenges. Security and Communication Networks, 7(12), 2728–2742.

    Article  Google Scholar 

  16. Zhang, X., et al. (2019). Intrusion detection and prevention in cloud, fog, and internet of things. Security and Communication Networks, 2019, 4529757.

    Google Scholar 

  17. Gai, K., et al. (2016). Intrusion detection techniques for mobile cloud computing in heterogeneous 5G. Security and Communication Networks, 9(16), 3049–3058.

    Article  Google Scholar 

  18. Yaseen, Q., et al. (2018). Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks. Transactions on Emerging Telecommunications Technologies, 29(4), e3183.

    Article  MathSciNet  Google Scholar 

  19. Alrawais, A., et al. (2017). Fog computing for the internet of things: Security and privacy issues. IEEE Internet Computing, 21(2), 34–42.

    Article  Google Scholar 

  20. Lin, F., et al. (2018). Fair resource allocation in an intrusion detection system for edge computing: Ensuring the security of Internet of Things devices. IEEE Consumer Electronics Magazine, 7(6), 45–50.

    Article  Google Scholar 

  21. Zhang, P. Y., Zhou, M. C., & Fortino, G. (2018). Security and trust issues in Fog computing: A survey. Future Generation Computer Systems, 88, 16–27.

    Article  Google Scholar 

  22. Liu, Y., Fieldsend, J. E., & Min, G. (2017). A framework of fog computing: Architecture, challenges, and optimization. IEEE Access, 5, 25445–25454.

    Article  Google Scholar 

  23. Soleymani, S. A., et al. (2017). A secure trust model based on fuzzy logic in vehicular ad hoc networks with fog computing. IEEE Access, 5, 15619–15629.

    Article  Google Scholar 

  24. Satyanarayanan, M. (2017). The emergence of edge computing. Computer, 50(1), 30–39.

    Article  Google Scholar 

  25. Byers, C. C. (2017). Architectural imperatives for fog computing: Use cases, requirements, and architectural techniques for fog-enabled iot networks. IEEE Communications Magazine, 55(8), 14–20.

    Article  Google Scholar 

  26. Wang, Y., Uehara, T., & Sasaki, R. (2015). Fog computing: Issues and challenges in security and forensics. In 2015 IEEE 39th annual computer software and applications conference (Vol. 3). IEEE.

    Google Scholar 

  27. Kumari, A., et al. (2019). Fog data analytics: A taxonomy and process model. Journal of Network and Computer Applications, 128, 90–104.

    Article  Google Scholar 

  28. Sam Greengard. (2018). SRT Interview: John Kindervag Says ‘Put Your Trust in Zero Trust’. Accessed 24 February, 2021. https://www.securityroundtable.org/john-kindervag-put-trust-zero-trust/

  29. Kindervag, J. (2010). Build security into your network’s DNA: The Zero Trust network architecture. Forrester Research Inc. Accessed 24 February, 2021. http://www.virtualstarmedia.com/downloads/Forrester_zero_trust_DNA.pdf

    Google Scholar 

  30. Wu, Y., Dai, H.-N., & Wang, H. (2021). Convergence of blockchain and edge computing for secure and scalable IIoT critical infrastructures in industry 4.0. IEEE Internet of Things Journal, 8(4), 2300–2317. https://doi.org/10.1109/JIOT.2020.3025916

    Article  Google Scholar 

  31. Yulei, W., Wang, Z., Ma, Y., & Leung, V. C. M. (2021). Deep reinforcement learning for blockchain in industrial IoT: A survey. Computer Networks, 191, 108004., ISSN 1389-1286. https://doi.org/10.1016/j.comnet.2021.108004

    Article  Google Scholar 

  32. Wu, Y. (2020). Cloud-edge orchestration for the internet-of-things: Architecture and AI-powered data processing. IEEE Internet of Things Journal, 8(16), 12792–12805. https://doi.org/10.1109/JIOT.2020.3014845

    Article  Google Scholar 

  33. Dhar, S., & Bose, I. (2020). Securing IoT devices using zero trust and blockchain. Journal of Organizational Computing and Electronic Commerce, 31(1), 18–34.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seema B. Joshi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Joshi, S.B., Panchal, S.D. (2022). A Systematic Survey on Security Challenges for Fog-Enabled Internet of Things (IoT) and Industrial Internet of Things (IIoT). In: Bhatt, C., Wu, Y., Harous, S., Villari, M. (eds) Security Issues in Fog Computing from 5G to 6G. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-031-08254-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-08254-2_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08253-5

  • Online ISBN: 978-3-031-08254-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics