Skip to main content
Log in

A Systematic Survey on Fog steered IoT: Architecture, Prevalent Threats and Trust Models

  • Published:
International Journal of Wireless Information Networks Aims and scope Submit manuscript

Abstract

Internet of Things (IoT) is considered as a scheme that consists of smart objects furnished with sensors, processing and networking technologies amalgamated to work together and provide an ecosystem in which smart services are delivered to end-users. Fog computing is the name given to a next level computing that extends cloud services closer to the end-devices. The main idea behind the introduction of this concept is the reduction of latency that exists in a typical IoT-cloud scenario. But, if on one side it accelerates the computing jobs; on the off-side, it increases the attack surface due to the presence of fog layer in between the two existing layers. The data gets computed near to the end-user, thus making it more vulnerable. Hence, it may be said that the threats that may not even exist in a cloud environment come into the picture at fog level. In this paper, we intend to thoroughly discuss various fog level architectures with the threats prevalent at this layer through systematic literature review (SLR). This article aims to classify systematically and statistically, analyse the prevalent attacks that occur in IoT-Fog scheme that are published between 2012- 2020. When two or more devices share information, trust plays a pre-eminent role. So, the authors have also considered ‘trust' in this study. The effect of trust on the different pillars of security is critically examined. Also, it is found that most of the researchers are emphasizing to prioritize trust in Fog- IoT scenario as it is a point of paramount significance.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Zheng, Xianrong, et al. "Cloud service negotiation in internet of things environment: A mixed approach." IEEE Transactions on Industrial Informatics 10.2 (2014): 1506-1515.

    Google Scholar 

  2. Botta, Alessio, et al. "Integration of cloud computing and internet of things: a survey." Futuregeneration computer systems 56 (2016): 684-700.

    Google Scholar 

  3. Cisco Fog Computing Solutions: Unleash the Power of the Internet of Things. https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-solutions.pdf. 2015.

  4. F. Bonomi, et al, Fog computing and its role in the internet of things. Proceedings of the first edition of the MCC workshop on Mobile cloud computing. ACM, New York, 2012.

  5. Alli, Adam A., and Muhammad Mahbub Alam. "The fog cloud of things: A survey on concepts, architecture, standards, tools, and applications." Internet of Things 9 (2020): 100177.

    Google Scholar 

  6. Dastjerdi, Amir Vahid, and Rajkumar Buyya. "Fog computing: Helping the Internet of Things realize its potential." Computer 49.8 (2016): 112-116.

    Google Scholar 

  7. Dastjerdi, Amir Vahid, et al. "Fog computing: Principles, architectures, and applications." Internet of Things. 2016. 61-75.

    Google Scholar 

  8. I. Stojmenovic, and W. Sheng, The fog computing paradigm: Scenarios and security issues, 2014 Federated Conference on Computer Science and Information Systems. IEEE, New York, 2014.

  9. Guan, Yunguo, et al. "Data Security and Privacy in Fog Computing." IEEE Network 99 (2018): 1-6.

    Google Scholar 

  10. Mukherjee, Mithun, et al. "Security and privacy in fog computing: Challenges." IEEE Access 5 (2017): 19293-19304.

    Google Scholar 

  11. S. Yi, L. Cheng, and L. Qun, A survey of fog computing: concepts, applications and issues. Proceedings of the 2015 workshop on mobile big data. ACM, New York, 2015.

  12. A. Yousefpour, et al., All one needs to know about fog computing and related edge computing paradigms, 2018.

  13. A. Aljumah, and T. A. Ahanger, Fog computing and security issues: a review. 2018 7th International Conference on Computers Communications and Control (ICCCC). IEEE, New York, 2018.

  14. F. Bonomi, et al., Fog computing: a platform for internet of things and analytics. Big data and internet of things: a roadmap for smart environments. Springer, Cham, pp. 169–186, 2014.

  15. Ni, Jianbing, et al. "Securing fog computing for internet of things applications: Challenges and solutions." IEEE Communications Surveys & Tutorials 20.1 (2017): 601-628.

    Google Scholar 

  16. Puthal, Deepak, et al. "Secure and sustainable load balancing of edge data centers in fog computing." IEEE Communications Magazine 56.5 (2018): 60-65.

    Google Scholar 

  17. Sharma, Pradip Kumar, Mu-Yen Chen, and Jong Hyuk Park. "A software defined fog node based distributed blockchain cloud architecture for IoT." IEEE Access 6 (2017): 115-124.

    Google Scholar 

  18. Huang, Cheng, Rongxing Lu, and Kim-Kwang Raymond Choo. "Vehicular fog computing: architecture, use case, and security and forensic challenges." IEEE Communications Magazine 55.11 (2017): 105-111

    Google Scholar 

  19. Zhang, PeiYun, MengChu Zhou, and Giancarlo Fortino. "Security and trust issues in Fog computing: A survey." Future Generation Computer Systems, 88 (2018): 16-27.

    Google Scholar 

  20. Mahmud, Redowan, Ramamohanarao Kotagiri, and Rajkumar Buyya. "Fog computing: A taxonomy, survey and future directions." Internet of everything. Springer, Singapore, 2018. 103-130.

    Google Scholar 

  21. Roman, Rodrigo, Javier Lopez, and Masahiro Mambo. "Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges." Future Generation Computer Systems 78 (2018): 680-698.

    Google Scholar 

  22. Khan, Saad, Simon Parkinson, and Yongrui Qin. "Fog computing security: a review of current applications and security solutions." Journal of Cloud Computing 6.1 (2017): 19.

    Google Scholar 

  23. S. Yi, Z. Qin, and Q. L. Security and privacy issues of fog computing: a survey. International conference on wireless algorithms, systems, and applications. Springer, Cham, 2015.

  24. Hassija, Vikas, et al. "A survey on IoT security: application areas, security threats, and solution architectures." IEEE Access 7 (2019): 82721-82743.

    Google Scholar 

  25. T. Alladi, V. Chamola, and S. Zeadally. Industrial control systems: Cyberattack trends and countermeasures. Computer Communications, 2020.

  26. Alladi, Tejasvi, et al. "Consumer IoT: Security vulnerability case studies and solutions." IEEE Consumer Electronics Magazine 9.2 (2020): 17-25.

    Google Scholar 

  27. Available at https://www.elsevier.com/__data/promis_misc/525444systematicreviewsguide.pdf

  28. S. J. Stolfo, M. B. Salem, A. D. Keromytis. Fog computing: mitigating insider data theft attacks in the cloud. 2012 IEEE symposium on security and privacy workshops. IEEE, New York, 2012.

  29. M. Sriram M. et al. A hybrid protocol to secure the cloud from insider threats. 2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM). IEEE, New York, 2014.

  30. Li, Zhi, et al. "A non-cooperative differential game-based security model in fog computing." China Communications 14.1 (2017): 180-189.

    Google Scholar 

  31. I. Butun, A. Sari, and P. Österberg. Security Implications of Fog Computing on the Internet of Things. 2019 IEEE International Conference on Consumer Electronics (ICCE). IEEE, New York, 2019.

  32. Diro, Abebe Abeshu, and Naveen Chilamkurti. "Distributed attack detection scheme using deep learning approach for Internet of Things." Future Generation Computer Systems 82 (2018): 761-768.

    Google Scholar 

  33. Sohal, Amandeep Singh, et al. "A cybersecurity framework to identify malicious edge device in fog computing and cloud-of-things environments." Computers & Security 74 (2018): 340-354.

    Google Scholar 

  34. Wang, Tian, et al. "Fog-based storage technology to fight with cyber threat." Future Generation Computer Systems 83 (2018): 208-218.

    Google Scholar 

  35. M. U. Shankarwar, and A. V. Pawar. Security and privacy in cloud computing: A survey. Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Springer, Cham, 2015.

  36. N. S. Khan, M. A. Chishti, and M. Saleem. Identifying various risks in cyber-security and providing a mind-map of network security issues to mitigate cyber-crimes. Proceedings of 2nd International Conference on Communication, Computing and Networking. Springer, Singapore, 2019.

  37. Maimó, Lorenzo Fernández, et al. "Dynamic management of a deep learning-based anomaly detection system for 5G networks." Journal of Ambient Intelligence and Humanized Computing (2018): 1-15.

    Google Scholar 

  38. Gandhi, Usha Devi, et al. "HIoTPOT: surveillance on IoT devices against recent threats." Wireless personal communications 103.2 (2018): 1179-1194.

    Google Scholar 

  39. Ziegeldorf, Jan Henrik, Oscar Garcia Morchon, and Klaus Wehrle. "Privacy in the Internet of Things: threats and challenges." Security and Communication Networks 7.12 (2014): 2728-2742.

    Google Scholar 

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

  41. Gai, Keke, et al. "Intrusion detection techniques for mobile cloud computing in heterogeneous 5G." Security and Communication Networks 9.16 (2016): 3049-3058.

    Google Scholar 

  42. Yaseen, Qussai, et al. "Leveraging fog computing and software defined systems for selective forwarding attacks detection in mobile wireless sensor networks." Transactions on Emerging Telecommunications Technologies 29.4 (2018): e3183.

    MathSciNet  Google Scholar 

  43. Alrawais, Arwa, et al. "Fog computing for the internet of things: Security and privacy issues." IEEE Internet Computing 21.2 (2017): 34-42.

    Google Scholar 

  44. Lin, Fuhong, et al. "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 (2018): 45-50.

    Google Scholar 

  45. Liu, Yang, Jonathan E. Fieldsend, and Geyong Min. "A framework of fog computing: Architecture, challenges, and optimization." IEEE Access 5 (2017): 25445-25454.

    Google Scholar 

  46. Soleymani, Seyed Ahmad, et al. "A secure trust model based on fuzzy logic in vehicular ad hoc networks with fog computing." IEEE Access 5 (2017): 15619-15629.

    Google Scholar 

  47. Satyanarayanan, Mahadev. "The emergence of edge computing." Computer 50.1 (2017): 30-39.

    Google Scholar 

  48. Byers, Charles C. "Architectural imperatives for fog computing: Use cases, requirements, and architectural techniques for fog-enabled iot networks." IEEE Communications Magazine 55.8 (2017): 14-20.

    Google Scholar 

  49. Y. Wang, T. Uehara, and R. Sasaki. Fog computing: Issues and challenges in security and forensics. 2015 IEEE 39th Annual Computer Software and Applications Conference. Vol. 3. IEEE, New York, 2015.

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

    Google Scholar 

  51. Puthal, Deepak, et al. "Fog Computing Security Challenges and Future Directions Energy and Security." IEEE Consumer Electronics Magazine 8.3 (2019): 92-96.

    MathSciNet  Google Scholar 

  52. Garcia Lopez, Pedro, et al. "Edge-centric computing: Vision and challenges." ACM SIGCOMM Computer Communication Review 45.5 (2015): 37-42.

    Google Scholar 

  53. P. Varshney, and Y. Simmhan. Demystifying fog computing: characterizing architectures, applications and abstractions. 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC). IEEE, New York, 2017

  54. N. Fernando, et al., Opportunistic fog for IoT: challenges and opportunities." IEEE Internet of Things Journal (2019).

  55. Martin, John Paul, et al. "Elucidating the challenges for the praxis of fog computing: An aspect‐based study." International Journal of Communication Systems 32.7 (2019): e3926.

    Google Scholar 

  56. S. Pearson, and A. Benameur. Privacy, security and trust issues arising from cloud computing. 2010 IEEE Second International Conference on Cloud Computing Technology and Science. IEEE, New York, 2010.

  57. Pearson, Siani. "Privacy, security and trust in cloud computing." Privacy and security for cloud computing. Springer, London, 2013. 3-42.

    Google Scholar 

  58. I. Souissi, N. B. Azzouna, and L. B. Said, A multi-level study of information trust models in WSN-assisted IoT, Computer Networks, (2019)

  59. P. Kochovski, et al. Trust management in a blockchain based fog computing platform with trustless smart oracles. Future Generation Computer Systems (2019).

  60. Nidhya, R., S. Karthik, and G. Smilarubavathy. "An End-to-End Secure and Energy-Aware Routing Mechanism for IoT-Based Modern Health Care System." Soft Computing and Signal Processing. Springer, Singapore, 2019. 379-388.

    Google Scholar 

  61. Tiburski, Ramao Tiago, et al. "Lightweight Security Architecture Based on Embedded Virtualization and Trust Mechanisms for IoT Edge Devices." IEEE Communications Magazine 57.2 (2019): 67-73.

    Google Scholar 

  62. Yao, Xuanxia, et al. "An Attribute Credential Based Public Key Scheme for Fog Computing in Digital Manufacturing." IEEE Transactions on Industrial Informatics 15.4 (2019): 2297-2307.

    Google Scholar 

  63. T. Wang et al. Energy-efficient and trustworthy data collection protocol based on mobile fog computing in Internet of Things. IEEE Transactions on Industrial Informatics (2019)

  64. T. D. Dang, and D. Hoang. A data protection model for fog computing. 2017 Second International Conference on Fog and Mobile Edge Computing (FMEC). IEEE, New York, 2017.

  65. T. Wang, et al., A novel trust mechanism based on fog computing in sensor–cloud system. Future Generation Computer Systems (2018).

  66. B. Tang, et al, A hierarchical distributed fog computing architecture for big data analysis in smart cities. Proceedings of the ASE Big Data & Social Informatics 2015. ACM, New York, 2015.

  67. C. C. Byers, and W. Patrick, Fog computing distributing data and intelligence for resiliency and scale necessary for IoT: The internet of things (ubiquity symposium), Ubiquity 4, 2015.

  68. Puliafito, Carlo, et al. "Fog computing for the internet of things: A Survey." ACM Transactions on Internet Technology (TOIT) 19.2 (2019): 18.

    Google Scholar 

  69. Sun, Xiang, and Nirwan Ansari. "EdgeIoT: Mobile edge computing for the Internet of Things." IEEE Communications Magazine 54.12 (2016): 22-29.

    Google Scholar 

  70. Sarkar, Subhadeep, Subarna Chatterjee, and Sudip Misra. "Assessment of the Suitability of Fog Computing in the Context of Internet of Things." IEEE Transactions on Cloud Computing 6.1 (2015): 46-59.

    Google Scholar 

  71. Munir, Arslan, Prasanna Kansakar, and Samee U. Khan. "IFCIoT: Integrated Fog Cloud IoT: A novel architectural paradigm for the future Internet of Things." IEEE Consumer Electronics Magazine 6.3 (2017): 74-82.

    Google Scholar 

  72. W. Lee, et al, A gateway based fog computing architecture for wireless sensors and actuator networks. 2016 18th International Conference on Advanced Communication Technology (ICACT). IEEE, New York, 2016.

  73. Hao, Zijiang, et al. "Challenges and software architecture for fog computing." IEEE Internet Computing 21.2 (2017): 44-53.

    Google Scholar 

  74. V. Gazis, et al., Components of fog computing in an industrial internet of things context, 2015 12th Annual IEEE International Conference on Sensing, Communication, and Networking-Workshops (SECON Workshops). IEEE, New York, 2015.

  75. Aazam, Mohammad, and Eui-Nam Huh. "Fog computing: The cloud-iot\/ioe middleware paradigm." IEEE Potentials 35.3 (2016): 40-44.

    Google Scholar 

  76. S. K. Datta, B. Christian, and H. Jerome, Fog computing architecture to enable consumer centric internet of things services, 2015 International Symposium on Consumer Electronics (ISCE). IEEE, New York, 2015.

  77. Chiang, Mung, and Tao Zhang. "Fog and IoT: An overview of research opportunities." IEEE Internet of Things Journal 3.6 (2016): 854-864.

    Google Scholar 

  78. Chang, Chii, Satish Narayana Srirama, and Rajkumar Buyya. "Indie fog: An efficient fog-computing infrastructure for the internet of things." Computer 50.9 (2017): 92-98.

    Google Scholar 

  79. B. Alturki, et al., Exploring the effectiveness of service decomposition in fog computing architecture for the Internet of Things. IEEE Transactions on Sustainable Computing, 2019.

  80. B. Donassolo, et al. Fog based framework for IoT service provisioning. 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, New York, 2019.

  81. Ning, Zhaolong, Jun Huang, and Xiaojie Wang. "Vehicular fog computing: Enabling real-time traffic management for smart cities." IEEE Wireless Communications 26.1 (2019): 87-93.

    Google Scholar 

  82. Gope, Prosanta, et al. "Anonymous Communications for Secure Device-to-Device-Aided Fog Computing: Architecture, Challenges, and Solutions." IEEE Consumer Electronics Magazine 8.3 (2019): 10-16.

    Google Scholar 

  83. B. Donassolo, et al. Fog based framework for IoT service orchestration, 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, New York, 2019.

  84. Tortonesi, Mauro, et al. "Taming the IoT data deluge: An innovative information-centric service model for fog computing applications." Future Generation Computer Systems 93 (2019): 888-902.

    Google Scholar 

  85. Naranjo, Paola G. Vinueza, et al. "FOCAN: A Fog-supported smart city network architecture for management of applications in the Internet of Everything environments." Journal of Parallel and Distributed Computing 132 (2019): 274-283.

    Google Scholar 

  86. Rahmani, Amir M., et al. "Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach." Future Generation Computer Systems 78 (2018): 641-658.

    Google Scholar 

  87. Luo, Juan, et al. "Container-based fog computing architecture and energy-balancing scheduling algorithm for energy iot." Future Generation Computer Systems 97 (2019): 50-60.

    Google Scholar 

  88. P. Maiti, et al. Mathematical modeling of QoS-aware fog computing architecture for IoT services. Emerging Technologies in Data Mining and Information Security. Springer, Singapore, pp. 13–21, 2019.

  89. W. Wang, et al., Data scheduling and resource optimization for fog computing architecture in industrial IoT. International Conference on Distributed Computing and Internet Technology. Springer, Cham, 2019.

  90. H. Dubey, et al.,Fog computing in medical internet-of-things: architecture, implementation, and applications. Handbook of Large-Scale Distributed Computing in Smart Healthcare. Springer, Cham, pp. 281–321, 2017.

  91. C. Tang, C, et al., Fog-enabled smart campus: architecture and challenges." International Conference on Security and Privacy in New Computing Environments. Springer, Cham, 2019.

  92. A. Mukherjee, et al., IoT-F2N: an energy-efficient architectural model for IoT using Femtolet-based fog network. The Journal of Supercomputing, pp. 1–22, 2019.

  93. H. Sun, et al., Energy and time efficient task offloading and resource allocation on the generic IoT-fog-cloud architecture. Peer-to-Peer Networking and Applications, pp. 1–16, 2019.

  94. J. Pacheco, and H. Salim, IoT security framework for smart cyber infrastructures. 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS* W). IEEE, New York, 2016.

  95. Diro, Abebe, and Naveen Chilamkurti. "Leveraging LSTM networks for attack detection in fog-to-things communications." IEEE Communications Magazine 56.9 (2018): 124-130.

    Google Scholar 

  96. Abeshu, Abebe, and Naveen Chilamkurti. "Deep learning: the frontier for distributed attack detection in fog-to-things computing." IEEE Communications Magazine 56.2 (2018): 169-175.

    Google Scholar 

  97. K. Lee, et al., On security and privacy issues of fog computing supported Internet of Things environment. 2015 6th International Conference on the Network of the Future (NOF). IEEE, New York, 2015.

  98. Li, Gaolei, et al. "Fog computing-enabled secure demand response for Internet of energy against collusion attacks using consensus and ACE." IEEE Access 6 (2018): 11278-11288.

    Google Scholar 

  99. H. He, et al., The security challenges in the IoT enabled cyber-physical systems and opportunities for evolutionary computing & other computational intelligence." 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, New York, 2016.

  100. A. MacDermott, et al., Securing Things in the Healthcare Internet of Things." 2019 Global IoT Summit (GIoTS). IEEE, New York, 2019.

  101. Alaba, Fadele Ayotunde, et al. "Internet of Things security: A survey." Journal of Network and Computer Applications 88 (2017): 10-28.

    Google Scholar 

  102. Dabbagh, Mehiar, and Ammar Rayes. "Internet of things security and privacy." Internet of Things From Hype to Reality. Springer, Cham, 2019. 211-238.

    Google Scholar 

  103. Modi, Chirag, et al. "A survey on security issues and solutions at different layers of Cloud computing." The journal of supercomputing 63.2 (2013): 561-592.

    Google Scholar 

  104. Stojmenovic, Ivan, et al. "An overview of fog computing and its security issues." Concurrency and Computation: Practice and Experience 28.10 (2016): 2991-3005.

    Google Scholar 

  105. T. Baker, et al., A secure fog‐based platform for SCADA‐based IoT critical infrastructure. Software: Practice and Experience, 2019.

  106. J. Liang, M. Zhang, and V. C. M. Leung. A reliable trust computing mechanism based on multi-source feedback and fog computing in social sensor cloud. IEEE Internet of Things Journal (2020).

  107. Hussain, Yasir, et al. "Context-Aware Trust and Reputation Model for Fog-Based IoT." IEEE Access 8 (2020): 31622-31632.

    Google Scholar 

  108. A. Thida, and T. Shwe. Process Provenance-based Trust Management in Collaborative Fog Environment. 2020 IEEE Conference on Computer Applications (ICCA). IEEE, New York, 2020.

  109. Alemneh, Esubalew, et al. "A two-way trust management system for fog computing." Future Generation Computer Systems 106 (2020): 206-220.

    Google Scholar 

  110. Al-Khafajiy, Mohammed, et al. "COMITMENT: A fog computing trust management approach." Journal of Parallel and Distributed Computing 137 (2020): 1-16.

    Google Scholar 

  111. Rahman, Fatin Hamadah, et al. "Find my trustworthy fogs: A fuzzy-based trust evaluation framework." Future Generation Computer Systems 109 (2020): 562-572.

    Google Scholar 

  112. W. B. Daoud, et al. Distributed trust-based monitoring approach for fog/cloud networks." Emerging Research in Data Engineering Systems and Computer Communications. Springer, Singapore, pp. 55–65, 2020.

  113. S. Y. Hashemi, and F. S. Aliee. Fuzzy, dynamic and trust based routing protocol for IoT. Journal of Network and Systems Management (2020).

Download references

Funding

No funding has been received for this research work.

Author information

Authors and Affiliations

Authors

Contributions

RV made substantial contributions to the design of the work and drafted it. SC revised it critically for important intellectual content. Both the authors approved the version to be published.

Corresponding author

Correspondence to Richa Verma.

Ethics declarations

Conflict of Interest

The authors declare that there exists no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Verma, R., Chandra, S. A Systematic Survey on Fog steered IoT: Architecture, Prevalent Threats and Trust Models. Int J Wireless Inf Networks 28, 116–133 (2021). https://doi.org/10.1007/s10776-020-00499-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10776-020-00499-z

Keywords

Navigation