Skip to main content
SpringerLink
Log in

Security Issues in Fog Environment: A Systematic Literature Review

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

Abstract

The potent concept of fog computing is currently attracting many researchers as it brings cloud services closer to the end-user. It also roots out some of the major limitations of the cloud scenario where there exists the need for extremely low latency. Despite its compelling advantages, fog computing is still an evolving paradigm that demands further research. Among all the other issues prevalent in fog computing, security is one of the burning issues. Fog nodes, being at the edge of the network, pose several security threats. The authors have thus conducted a systematic literature review (SLR) on security issues in fog computing scenario. Initially, the prevalent security issues are identified through an in-depth survey and then the available literature per security issue is analyzed systematically. This SLR reveals that the security in/through fog scenario is being addressed by the researchers all over the globe. But, the approaches with respect to fog environment still lack methods to evaluate security aspects. Though most of the researchers are prioritizing the consideration of security aspects at fog level, there still exists a need to consider fog computing security as an area of serious concern.

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

Access this article

Log in via an institution

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

Primary studies included

  1. X. Liu, et al., Security and privacy challenges for internet-of-things and fog computing, Wireless Communications and Mobile Computing, 2018.

  2. R. Mahmud, R. Kotagiri and R. Buyya, Fog computing: a taxonomy, survey and future directions. in Internet of everything, pp. 103–130. Springer, Singapore, 2018.

  3. H. Noura, et al., Preserving data security in distributed fog computing, Ad Hoc Networks, Vol. 94, p. 101937, 2019.

    Google Scholar 

  4. D. Puthal, S. P. Mohanty, S. A. Bhavake, G. Morgan and R. Ranjan, Fog computing security challenges and future directions [energy and security], IEEE Consumer Electronics Magazine, Vol. 8, No. 3, pp. 92–96, 2019.

    Google Scholar 

  5. C. S. R. Prabhu, Fog security and privacy. Fog computing, deep learning and big data analytics-research directions, pp. 43–46, Springer, Singapore, 2019.

  6. M. Abdel-Basset, G. Manogaran and M. Mohamed, A neutrosophic theory-based security approach for fog and mobile-edge computing, Computer Networks, Vol. 157, pp. 122–132, 2019.

    Google Scholar 

  7. I. Butun, A. Sari and P. Österberg, Security implications of fog computing on the internet of things, in 2019 IEEE International Conference on Consumer Electronics (ICCE), IEEE, New York, 2019.

  8. T. Wang, et al., Solving coupling security problem for sustainable sensor-cloud systems based on fog computing, IEEE Transactions on Sustainable Computing, 2019.

  9. S. Alharbi, et al., FOCUS: a fog computing-based security system for the Internet of Things, in 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC), IEEE, New York, 2018.

  10. A. Alrawais, et al., Fog computing for the internet of things: security and privacy issues, IEEE Internet Computing, Vol. 21, No. 2, pp. 34–42, 2017.

    Google Scholar 

  11. R. Chaudhary, N. Kumar and S. Zeadally, Network service chaining in fog and cloud computing for the 5G environment: data management and security challenges, IEEE Communications Magazine, Vol. 55, No. 11, pp. 114–122, 2017.

    Google Scholar 

  12. Y. Guan, et al., Data security and privacy in fog computing, IEEE Network, Vol. 32, No. 5, pp. 106–111, 2018.

    Google Scholar 

  13. P. Hu, et al., Security and privacy preservation scheme of face identification and resolution framework using fog computing in internet of things, IEEE Internet of Things Journal, Vol. 4, No. 5, pp. 1143–1155, 2017.

    Google Scholar 

  14. H. A. Al Hamid, et al., A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography, IEEE Access, Vol. 5, pp. 22313–22328, 2017.

    Google Scholar 

  15. W. Abdul, et al., Biometric security through visual encryption for fog edge computing, IEEE Access, Vol. 5, pp. 5531–5538, 2017.

    Google Scholar 

  16. M. Aazam, S. Zeadally and K. A. Harras, Fog computing architecture, evaluation, and future research directions, IEEE Communications Magazine, Vol. 56, No. 5, pp. 46–52, 2018.

    Google Scholar 

  17. M. Mukherjee, et al., Security and privacy in fog computing: Challenges, IEEE Access, Vol. 5, pp. 19293–19304, 2017.

    Google Scholar 

  18. V. K. Sehgal, et al., Smart Human Security Framework Using Internet of Things, Cloud and Fog Computing. Intelligent Distributed Computing, SpringerCham, 2015. pp. 251–263.

    Google Scholar 

  19. J. Ni, et al., Securing fog computing for internet of things applications: challenges and solutions, IEEE Communications Surveys & Tutorials, Vol. 20, No. 1, pp. 601–628, 2017.

    Google Scholar 

  20. S. N. Shirazi, et al., The extended cloud: review and analysis of mobile edge computing and fog from a security and resilience perspective, IEEE Journal on Selected Areas in Communications, Vol. 35, No. 11, pp. 2586–2595, 2017.

    Google Scholar 

  21. J. Ni, et al., Security, privacy, and fairness in fog-based vehicular crowdsensing, IEEE Communications Magazine, Vol. 55, No. 6, pp. 146–152, 2017.

    Google Scholar 

  22. B. Mukherjee, et al., Flexible IoT security middleware for end-to-end cloud–fog communication, Future Generation Computer Systems, Vol. 87, pp. 688–703, 2018.

    Google Scholar 

  23. S. Khan, S. Parkinson and Y. Qin, Fog computing security: a review of current applications and security solutions, Journal of Cloud Computing, Vol. 6, No. 1, p. 19, 2017.

    Google Scholar 

  24. B. Mukherjee, R. L. Neupane and P. Calyam, End-to-end IoT security middleware for cloud-fog communication. in 2017 IEEE 4th International Conference on Cyber Security and Cloud Computing (CSCloud). IEEE, New York, 2017.

  25. S. Yi, Z. Qin and Q. Li, Security and privacy issues of fog computing: a survey, in International Conference on Wireless Algorithms, Systems, and Applications. Springer, Cham, 2015.

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

  27. S. P. Singh, et al., Fog computing: from architecture to edge computing and big data processing, The Journal of Supercomputing, Vol. 75, No. 4, pp. 2070–2105, 2019.

    Google Scholar 

  28. R. Roman, J. Lopez and M. Mambo, Mobile edge computing, fog et al.: a survey and analysis of security threats and challenges, Future Generation Computer Systems, Vol. 78, pp. 680–698, 2018.

    Google Scholar 

  29. C. Huang, R. Lu and K. K. R. Choo, Vehicular fog computing: architecture, use case, and security and forensic challenges, IEEE Communications Magazine, Vol. 55, No. 11, pp. 105–111, 2017.

    Google Scholar 

  30. X. Masip-Bruin, et al., Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems, IEEE Wireless Communications, Vol. 23, No. 5, pp. 120–128, 2016.

    Google Scholar 

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

  32. P. Kumar, N. Zaidi and T. Choudhury, Fog computing: common security issues and proposed countermeasures.” in 2016 International Conference System Modeling & Advancement in Research Trends (SMART), IEEE, New York, 2016.

  33. P. Zhang, M. Zhou and G. Fortino, Security and trust issues in Fog computing: a survey, Future Generation Computer Systems, Vol. 88, pp. 16–27, 2018.

    Google Scholar 

  34. J. Wu, et al., FCSS: fog computing-based content-aware filtering for security services in information centric social networks, IEEE Transactions on Emerging Topics in Computing, 2017.

  35. K. Fan, et al., Efficient and privacy preserving access control scheme for fog-enabled IoT, Future Generation Computer Systems, Vol. 99, pp. 134–142, 2019.

    Google Scholar 

  36. S. Salonikias, I. Mavridis and D. Gritzalis, Access control issues in utilizing fog computing for transport infrastructure. in International Conference on Critical Information Infrastructures Security, Springer, Cham, 2015.

  37. Z. Wang, Leakage resilient ID-based proxy re-encryption scheme for access control in fog computing, Future Generation Computer Systems, Vol. 87, pp. 679–685, 2018.

    Google Scholar 

  38. Z. Yu, et al., Towards leakage-resilient fine-grained access control in fog computing, Future Generation Computer Systems, Vol. 78, pp. 763–777, 2018.

    Google Scholar 

  39. K. Xue, et al., Fog-aided verifiable privacy preserving access control for latency-sensitive data sharing in vehicular cloud computing, IEEE Network, Vol. 32, No. 3, pp. 7–13, 2018.

    Google Scholar 

  40. X. Wang, et al., Privacy-aware efficient fine-grained data access control in Internet of medical things-based fog computing, IEEE Access, Vol. 6, pp. 47657–47665, 2018.

    Google Scholar 

  41. P. Zhang, et al., An efficient access control scheme with outsourcing capability and attribute update for fog computing, Future Generation Computer Systems, Vol. 78, pp. 753–762, 2018.

    Google Scholar 

  42. K. Gai, M. Qiu and M. Liu, Privacy-preserving access control using dynamic programming in fog computing, in 2018 IEEE 4th International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing, (HPSC) and IEEE International Conference on Intelligent Data and Security (IDS), IEEE, New York, 2018.

  43. Q. Huang, Y. Yang and L. Wang, Secure data access control with ciphertext update and computation outsourcing in fog computing for Internet of Things, IEEE Access, Vol. 5, pp. 12941–12950, 2017.

    Google Scholar 

  44. D. Li, et al., Efficient CCA2 secure flexible and publicly-verifiable fine-grained access control in fog computing, IEEE Access, Vol. 7, pp. 11688–11697, 2019.

    Google Scholar 

  45. L. Zhu, et al., Privacy-preserving authentication and data aggregation for fog-based smart grid, IEEE Communications Magazine, Vol. 57, No. 6, pp. 80–85, 2019.

    Google Scholar 

  46. Jia, X, et al. “A Provably Secure and Efficient Identity-Based Anonymous Authentication Scheme for Mobile Edge Computing.” IEEE Systems Journal, 2019.

  47. M. Ma, et al., An efficient and provably-secure authenticated key agreement protocol for fog-based vehicular ad-hoc networks, IEEE Internet of Things Journal, Vol. 6, No. 5, pp. 8065–8075, 2019.

    Google Scholar 

  48. M. A. Ferrag, et al., Privacy-preserving schemes for fog-based IoT applications: threat models, solutions, and challenges. in 2018 International Conference on Smart Communications in Network Technologies (SaCoNeT). IEEE, New York, 2018.

  49. A. A. Diro, N. Chilamkurti and N. Kumar, Lightweight cybersecurity schemes using elliptic curve cryptography in publish-subscribe fog computing, Mobile Networks and Applications, Vol. 22, No. 5, pp. 848–858, 2017.

    Google Scholar 

  50. S. Chaba, et al., Secure and efficient key delivery in VANET using cloud and fog computing. in 2017 International Conference on Computer, Communications and Electronics (Comptelix), IEEE, New York, 2017.

  51. S. Alharbi, et al., Secure the internet of things with challenge response authentication in fog computing. in 2017 IEEE 36th International Performance Computing and Communications Conference (IPCCC). IEEE, New York, 2017.

  52. P. Gope, et al., Lightweight and physically secure anonymous mutual authentication protocol for real-time data access in industrial wireless sensor networks, IEEE Transactions on Industrial Informatics, 2019.

  53. P. Hu, et al., Survey on fog computing: architecture, key technologies, applications and open issues, Journal of Network and Computer Applications, Vol. 98, pp. 27–42, 2017.

    Google Scholar 

  54. X. Yao, et al., An attribute credential based public key scheme for fog computing in digital manufacturing, IEEE Transactions on Industrial Informatics, Vol. 15, No. 4, pp. 2297–2307, 2019.

    Google Scholar 

  55. Y. Imine, et al., MASFOG: an efficient mutual authentication scheme for fog computing architecture. in 2018 17th IEEE International Conference on Trust, Security and Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). IEEE, New York, 2018.

  56. O. Salman, et al., Identity-based authentication scheme for the internet of things. in 2016 IEEE Symposium on Computers and Communication (ISCC). IEEE, New York, 2016.

  57. F. Wang, et al., LAMANCO: a lightweight anonymous mutual authentication scheme for n-times computing offloading in IoT, IEEE Internet of Things Journal, 2018.

  58. J. Shen, et al., Lightweight authentication and matrix-based key agreement scheme for healthcare in fog computing, Peer-to-Peer Networking and Applications, Vol. 12, No. 4, pp. 924–933, 2019.

    Google Scholar 

  59. P. Wang, et al., A cross-age face recognition approach using fog computing architecture for user authentication on mobile devices. in 2018 IEEE 15th International Conference on e-Business Engineering (ICEBE). IEEE, New York, 2018.

  60. M. Wazid, et al., Design of secure key management and user authentication scheme for fog computing services, Future Generation Computer Systems, Vol. 91, pp. 475–492, 2019.

    Google Scholar 

  61. S. Zahra, et al., Fog computing over iot: a secure deployment and formal verification, IEEE Access, Vol. 5, pp. 27132–27144, 2017.

    Google Scholar 

  62. Y. Jiang, et al., Ciphertext-policy attribute-based encryption against key-delegation abuse in fog computing, Future Generation Computer Systems, Vol. 78, pp. 720–729, 2018.

    Google Scholar 

  63. J. Kang, et al., Privacy-preserved pseudonym scheme for fog computing supported internet of vehicles, IEEE Transactions on Intelligent Transportation Systems, Vol. 19, No. 8, pp. 2627–2637, 2017.

    Google Scholar 

  64. H. Kim and E. A. Lee, Authentication and authorization for the Internet of Things, IT Professional, Vol. 19, No. 5, pp. 27–33, 2017.

    Google Scholar 

  65. W. Shi, et al., Edge computing: vision and challenges, IEEE Internet of Things Journal, Vol. 3, No. 5, pp. 637–646, 2016.

    Google Scholar 

  66. S. J. Stolfo, M. B. Salem and A. D. Keromytis, Fog computing: Mitigating insider data theft attacks in the cloud, in 2012 IEEE Symposium on Security and Privacy Workshops, IEEE, New York, 2012.

  67. J. Li, et al., EHOPES: data-centered Fog platform for smart living. in 2015 International Telecommunication Networks and Applications Conference (ITNAC). IEEE, New York, 2015.

  68. B. W. Kwon, J. Kang and J. H. Park, A Fog Computing-Based Automotive Data Overload Protection System with Real-Time Analysis. Advanced Multimedia and Ubiquitous Engineering, SingaporeSpringer, 2018. pp. 693–696.

    Google Scholar 

  69. W. Shi and S. Dustdar, The promise of edge computing, Computer, Vol. 49, No. 5, pp. 78–81, 2016.

    Google Scholar 

  70. T. Wang, et al., A three-layer privacy preserving cloud storage scheme based on computational intelligence in fog computing, IEEE Transactions on Emerging Topics in Computational Intelligence, Vol. 2, No. 1, pp. 3–12, 2018.

    Google Scholar 

  71. Q. Wang, et al., PCP: a privacy-preserving content-based publish–subscribe scheme with differential privacy in fog computing, IEEE Access, Vol. 5, pp. 17962–17974, 2017.

    Google Scholar 

  72. C. Piao, et al., Privacy-preserving governmental data publishing: A fog-computing-based differential privacy approach, Future Generation Computer Systems, Vol. 90, pp. 158–174, 2019.

    Google Scholar 

  73. M. Altulyan, et al., A unified framework for data integrity protection in people-centric smart cities, Multimedia Tools and Applications, pp. 1–14, 2019.

  74. A. G. Finogeev, D. S. Parygin and A. A. Finogeev, The convergence computing model for big sensor data mining and knowledge discovery, Human-Centric Computing and Information Sciences, Vol. 7, No. 1, p. 11, 2017.

    Google Scholar 

  75. C. Zuo, et al., CCA-secure ABE with outsourced decryption for fog computing, Future Generation Computer Systems, Vol. 78, pp. 730–738, 2018.

    Google Scholar 

  76. C. Esposito, et al., Challenges of connecting edge and cloud computing: a security and forensic perspective, IEEE Cloud Computing, Vol. 4, No. 2, pp. 13–17, 2017.

    Google Scholar 

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

  78. P. Illy, et al., Securing Fog-to-Things Environment Using Intrusion Detection System Based On Ensemble Learning. arXiv preprint arXiv:1901.10933, 2019.

  79. Q. Yaseen, et al., A fog computing based system for selective forwarding detection in mobile wireless sensor networks, in 2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS* W), IEEE, New York, 2016.

  80. S. Zhao, et al., A dimension reduction model and classifier for anomaly-based intrusion detection in internet of things. in 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech). IEEE, New York, 2017.

  81. A. Abeshu and N. Chilamkurti, Deep learning: the frontier for distributed attack detection in fog-to-things computing, IEEE Communications Magazine, Vol. 56, No. 2, pp. 169–175, 2018.

    Google Scholar 

  82. D. A. Chekired, L. Khoukhi and H. T. Mouftah, Fog-based distributed intrusion detection system against false metering attacks in smart grid. in ICC 2019-2019 IEEE International Conference on Communications (ICC), IEEE, New York, 2019.

  83. I. Stojmenovic and S. Wen, The fog computing paradigm: scenarios and security issues, in 2014 Federated Conference on Computer Science and Information Systems. IEEE, New York, 2014.

  84. S. Shen, et al., Multistage signaling game-based optimal detection strategies for suppressing malware diffusion in fog-cloud-based IoT networks, IEEE Internet of Things Journal, Vol. 5, No. 2, pp. 1043–1054, 2018.

    Google Scholar 

  85. D. Koo and J. Hur, Privacy-preserving deduplication of encrypted data with dynamic ownership management in fog computing, Future Generation Computer Systems, Vol. 78, pp. 739–752, 2018.

    Google Scholar 

  86. R. Yang, et al., Position based cryptography with location privacy: a step for fog computing, Future Generation Computer Systems, Vol. 78, pp. 799–806, 2018.

    Google Scholar 

  87. Sultan Basudan, Xiaodong Lin and Karthik Sankaranarayanan, A privacy-preserving vehicular crowdsensing-based road surface condition monitoring system using fog computing, IEEE Internet of Things Journal, Vol. 4, No. 3, pp. 772–782, 2017.

    Google Scholar 

  88. X. Liu, et al., Hybrid privacy-preserving clinical decision support system in fog–cloud computing, Future Generation Computer Systems, Vol. 78, pp. 825–837, 2018.

    Google Scholar 

  89. T. Wang, et al., Trajectory privacy preservation based on a fog structure for cloud location services, IEEE Access, Vol. 5, pp. 7692–7701, 2017.

    Google Scholar 

  90. E. M. Schooler, et al., An architectural vision for a data-centric IoT: rethinking things, trust and clouds, in 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), IEEE, New York, 2017.

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

  92. W. B. Daoud, et al., TACRM: trust access control and resource management mechanism in fog computing, Human-centric Computing and Information Sciences, Vol. 9, No. 1, p. 28, 2019.

    Google Scholar 

  93. S. Pearson, Privacy, Security and Trust in Cloud Computing. Privacy and Security for Cloud Computing, SpringerLondon, 2013. pp. 3–42.

    Google Scholar 

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

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

    Google Scholar 

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

  97. R. T. Tiburski, et al., Lightweight security architecture based on embedded virtualization and trust mechanisms for IoT edge devices, IEEE Communications Magazine, Vol. 57, No. 2, pp. 67–73, 2019.

    Google Scholar 

  98. R. Beregi, G. Pedone and I. Mezgár, A novel fluid architecture for cyber-physical production systems, International Journal of Computer Integrated Manufacturing, Vol. 32, No. 4–5, pp. 340–351, 2019.

    Google Scholar 

  99. S. Sareen, S. K. Gupta and S. K. Sood, An intelligent and secure system for predicting and preventing Zika virus outbreak using Fog computing, Enterprise Information Systems, Vol. 11, No. 9, pp. 1436–1456, 2017.

    Google Scholar 

  100. S. K. Erskine and K. M. Elleithy, Real-time detection of DoS attacks in IEEE 802.11 p using fog computing for a secure intelligent vehicular network, Electronics, Vol. 8, No. 7, p. 776, 2019.

    Google Scholar 

  101. S. Svorobej, et al., Simulating fog and edge computing scenarios: An overview and research challenges, Future Internet, Vol. 11, No. 3, p. 55, 2019.

    Google Scholar 

  102. A. Muthanna, et al., Secure and reliable IoT networks using fog computing with software-defined networking and blockchain, Journal of Sensor and Actuator Networks, Vol. 8, No. 1, p. 15, 2019.

    Google Scholar 

  103. N. Abbas, et al., A mechanism for securing IoT-enabled applications at the fog layer, Journal of Sensor and Actuator Networks, Vol. 8, No. 1, p. 16, 2019.

    MathSciNet  Google Scholar 

  104. S. K. Erskine and K. M. Elleithy, Secure intelligent vehicular network using fog computing, Electronics, Vol. 8, No. 4, p. 455, 2019.

    Google Scholar 

  105. B. Sudqi Khater, et al., A lightweight perceptron-based intrusion detection system for fog computing, Applied Sciences, Vol. 9, No. 1, p. 178, 2019.

    Google Scholar 

  106. R. Fantacci, et al., False data detection for fog and internet of things networks, Sensors, Vol. 19, No. 19, p. 4235, 2019.

    Google Scholar 

  107. R. Sandhu, A. S. Sohal and S. K. Sood, Identification of malicious edge devices in fog computing environments, Information Security Journal: A Global Perspective, Vol. 26, No. 5, pp. 213–228, 2017.

    Google Scholar 

  108. Z. Zhang, et al., e-DMDAV: a new privacy preserving algorithm for wearable enterprise information systems, Enterprise Information Systems, Vol. 12, No. 4, pp. 492–504, 2018.

    Google Scholar 

  109. C. Puliafito, E. Mingozzi, F. Longo, A. Puliafito and O. Rana, Fog computing for the internet of things: a survey, ACM Transactions on Internet Technology (TOIT), Vol. 19, No. 2, pp. 1–41, 2019.

    Google Scholar 

  110. C. M. Chen, Y. Huang, K. H. Wang, S. Kumari and M. E. Wu, A secure authenticated and key exchange scheme for fog computing, Enterprise Information Systems, pp. 1–16, 2020.

  111. U. Ogiela, M. Takizawa and L. Ogiela, Linguistic-Based Security in Fog and Cloud Computing. in International Conference on Emerging Internetworking, Data & Web Technologies, pp. 120–127, Springer, Cham, February 2019.

  112. G. Javadzadeh and A. M. Rahmani, Fog computing applications in smart cities: a systematic survey, Wireless Networks, pp. 1–25, 2019.

  113. T. Khalid, A. N. Khan, M. Ali, A. Adeel and J. Shuja, A fog-based security framework for intelligent traffic light control system, Multimedia Tools and Applications, Vol. 78, No. 17, pp. 24595–24615, 2019.

    Google Scholar 

  114. R. Huang, Y. Sun, C. Huang, G. Zhao and Y. Ma, A survey on fog computing. in International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, pp. 160–169, Springer, Cham, July 2019.

  115. S. Rani, and P. Saini, Fog computing: applications and secure data aggregation, in Handbook of Computer Networks and Cyber Security, pp. 475–492, Springer, Cham, 2020.

  116. S. Pešić, M. Radovanović, M. Ivanović, C. Badica, M. Tošić, O. Iković and D. Bošković, CAAVI-RICS model for analyzing the security of fog computing systems. in International Symposium on Intelligent and Distributed Computing, pp. 23–34, Springer, Cham, October 2019.

  117. X. Shen, L. Zhu, C. Xu, K. Sharif and R. Lu, A privacy-preserving data aggregation scheme for dynamic groups in fog computing, Information Sciences, Vol. 514, pp. 118–130, 2020.

    Google Scholar 

  118. Y. He, J. Ni, B. Niu, F. Li and X. S. Shen, Privbus: A privacy-enhanced crowdsourced bus service via fog computing, Journal of Parallel and Distributed Computing, Vol. 135, pp. 156–168, 2020.

    Google Scholar 

  119. E. Alemneh, S. M. Senouci, P. Brunet and T. Tegegne, A two-way trust management system for fog computing, Future Generation Computer Systems, 2019.

  120. M. Al-khafajiy, T. Baker, M. Asim, Z. Guo, R. Ranjan, A. Longo, D. Puthal and M. Taylor, COMITMENT: a fog computing trust management approach, Journal of Parallel and Distributed Computing, Vol. 137, pp. 1–16, 2020.

    Google Scholar 

  121. M. M. Ahsan, I. Ali, M. Imran, M. Y. I. Idris, S. Khan and A. Khan, A fog-centric secure cloud storage scheme, IEEE Transactions on Sustainable Computing, 2019.

  122. T. Almehmadi, S. Alshehri and S. Tahir, A secure fog-cloud based architecture for MIoT. in 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS), pp. 1–6, IEEE, New York, May 2019.

  123. B. E. N. Arij, A. B. I. D. Mohamed and A. Meddeb, SAMAFog: Service-Aware Mutual Authentication Fog-based Protocol. in 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 1049–1054, IEEE, New York, June 2019.

  124. Z. Bakhshi and A. Balador, An overview on security and privacy challenges and their solutions in fog-based vehicular application, in 2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC Workshops), pp. 1–7, IEEE, New York, September 2019.

  125. M. Barbareschi, A. De Benedictis, E. La Montagna, A. Mazzeo and N. Mazzocca, PUF-enabled authentication-as-a-service in fog-IoT systems. in 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), pp. 58–63, IEEE, New York, June 2019.

  126. D. Belli, S. Chessa, B. Kantarci and L. Foschini, Toward fog-based mobile crowdsensing systems: state of the art and opportunities, IEEE Communications Magazine, Vol. 57, No. 12, pp. 78–83, 2019.

    Google Scholar 

  127. M. De Donno and N. Dragoni, Combining antibiotic with fog computing: antibiotic 2.0. in 2019 IEEE 3rd International Conference on Fog and Edge Computing (ICFEC), pp. 1–6, IEEE, New York, May 2019.

  128. M. Du, K. Wang, X. Liu, S. Guo and Y. Zhang, A differential privacy-based query model for sustainable fog data centers. IEEE Transactions on Sustainable Computing, 2017.

  129. B. Gu, X. Wang, Y. Qu, J. Jin, Y. Xiang and L. Gao, Context-aware privacy preservation in a hierarchical fog computing system. in ICC 2019-2019 IEEE International Conference on Communications (ICC), pp. 1–6, IEEE, New York, May 2019.

  130. N. Hassan, K. L. A. Yau and C. Wu, Edge computing in 5G: a review, IEEE Access, Vol. 7, pp. 127276–127289, 2019.

    Google Scholar 

  131. M. Heydari, A. Mylonas, V. Katos, E. Balaguer-Ballester, V. H. F. Tafreshi and E. Benkhelifa, Uncertainty-aware authentication model for fog computing in IoT. in 2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC), pp. 52–59, IEEE, New York, June 2019.

  132. H. M. R. Al-Khafaji, E. S. Alomari and H. S. Majdi, Secured environment for cloud integrated fog and mist architecture. in 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech), pp. 112–116, IEEE, New York, October 2019.

  133. P. Tedeschi and S. Sciancalepore, Edge and fog computing in critical infrastructures: analysis, security threats, and research challenges. in 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), pp. 1–10, IEEE, New York, June 2019.

  134. T. Wang, J. Zhou, A. Liu, M. Z. A. Bhuiyan, G. Wang and W. Jia, Fog-based computing and storage offloading for data synchronization in IoT, IEEE Internet of Things Journal, Vol. 6, No. 3, pp. 4272–4282, 2018.

    Google Scholar 

Other references

  1. ‘Internet of Things-Cisco.’ https://www.cisco.com/c/dam/en/us/products/collateral/se/internet-of-things/at-a-glance-c45-731471.pdf. Accessed 15 May 2019.

  2. Marcus Gomes and Miguel L. Pardal, Cloud vs Fog: assessment of alternative deployments for a latency-sensitive IoT application, Procedia Computer Science, Vol. 130, pp. 488–495, 2018.

    Google Scholar 

  3. M. Chiang and Z. Tao, Fog and IoT: an overview of research opportunities, IEEE Internet of Things Journal, Vol. 3, No. 6, pp. 854–864, 2016.

    Google Scholar 

  4. A. V. Dastjerdi and R. Buyya, Fog computing: helping the Internet of Things realize its potential, Computer, Vol. 49, No. 8, pp. 112–116, 2016.

    Google Scholar 

  5. ‘Security a prime concern in IoT.’ https://www.geospatialworld.net/article/security-a-prime-concern-in-iot. Accessed 27 May 2019.

  6. 48% of companies can detect IoT device breaches. https://www.mediapost.com/publications/article/330778/48-of-companies-can-detect-iot-device-breaches-s.html. Accessed 27 May 2019.

  7. Top 4 Shocking IoT Security Breaches of 2018. https://www.pentasecurity.com/blog/4-shocking-iot-security-breaches-2018/. Accessed 28 May 2019.

  8. S. P. Singh, et al., Fog computing: from architecture to edge computing and big data processing, The Journal of Supercomputing, pp. 1–36, 2018.

  9. K. K. R. Choo, et al., A foggy research future: advances and future opportunities in fog computing research, pp. 677–679, 2018.

  10. A. Dasgupta and A. Q. Gill, Fog computing challenges: a systematic review, in Australasian Conference on Information Systems Dasgupta & Gil1, 2017.

  11. A. Yousefpour, et al., All one needs to know about fog computing and related edge computing paradigms: a complete survey, Journal of Systems Architecture, 2019.

  12. A. T. Thien and R. Colomo-Palacios, A systematic literature review of fog computing, NOKOBIT 2016, Bergen, 28–30 Nov. NOKOBIT, Bibsys Open Journal Systems, Vol. 24, No. 1, 2016.

  13. V. Pande, C. Marlecha and S. Kayte, A review-fog computing and its role in the Internet of Things, Int. J. Eng. Res. Appl., Vol. 6, No. 10, pp. 2248–9622, 2016.

    Google Scholar 

  14. C. Mouradian, et al., A comprehensive survey on fog computing: State-of-the-art and research challenges, IEEE Communications Surveys & Tutorials, Vol. 20, No. 1, pp. 416–464, 2017.

    Google Scholar 

  15. M. Aazam, S. Zeadally and K. A. Harras, Offloading in fog computing for IoT: Review, enabling technologies, and research opportunities, Future Generation Computer Systems, Vol. 87, pp. 278–289, 2018.

    Google Scholar 

  16. F. Al-Doghman, et al., A review on Fog Computing technology. in 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE, New York, 2016.

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

  18. H. F. Atlam, R. J. Walters and G. B. Wills, Fog computing and the internet of things: a review, Big Data and Cognitive Computing, Vol. 2, No. 2, p. 10, 2018.

    Google Scholar 

  19. 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, pp. 169–186. Springer, Cham, 2014. .

  20. H. T. Dinh, et al., A survey of mobile cloud computing: architecture, applications, and approaches, Wireless Communications and Mobile Computing, Vol. 13, No. 18, pp. 1587–1611, 2013.

    Google Scholar 

  21. R. K. Naha, et al., Fog computing: survey of trends, architectures, requirements, and research directions, IEEE Access, Vol. 6, pp. 47980–48009, 2018.

    Google Scholar 

  22. S. Kunal, A. Saha and R. Amin, An overview of cloud-fog computing: Architectures, applications with security challenges, Security and Privacy, Vol. 2, No. 4, p. e72, 2019.

    Google Scholar 

  23. M. Mukherjee, L. Shu and D. Wang, Survey of fog computing: fundamental, network applications, and research challenges, IEEE Communications Surveys & Tutorials, Vol. 20, No. 3, pp. 1826–1857, 2018.

    Google Scholar 

  24. O. Osanaiye, et al., From cloud to fog computing: a review and a conceptual live VM migration framework, IEEE Access, Vol. 5, pp. 8284–8300, 2017.

    Google Scholar 

  25. O. Salman, et al., IoT survey: an SDN and fog computing perspective, Computer Networks, Vol. 143, pp. 221–246, 2018.

    Google Scholar 

  26. P. Zhang, et al., A survey on access control in fog computing, IEEE Communications Magazine, Vol. 56, No. 2, pp. 144–149, 2018.

    Google Scholar 

  27. H. Dubey, et al., Fog data: enhancing telehealth big data through fog computing. in Proceedings of the ASE bigdata & socialinformatics 2015, ACM, 2015.

  28. F. A. Kraemer, et al., Fog computing in healthcare—a review and discussion, IEEE Access, Vol. 5, pp. 9206–9222, 2017.

    Google Scholar 

  29. C. Perera, et al., Fog computing for sustainable smart cities: a survey, ACM Computing Surveys (CSUR), Vol. 50, No. 3, p. 32, 2017.

    Google Scholar 

  30. V. Gupta, et al., An energy-efficient fog-cloud based architecture for healthcare, Journal of Statistics and Management Systems, Vol. 21, No. 4, pp. 529–537, 2018.

    Google Scholar 

  31. J. Kharel, H. T. Reda and S. Y. Shin, Fog computing-based smart health monitoring system deploying Lora wireless communication, IETE Technical Review, Vol. 36, No. 1, pp. 69–82, 2019.

    Google Scholar 

  32. B. Kitchenham and S. Charters, Guidelines for performing systematic literature reviews in software engineering, in Engineering, Vol. 2, p. 1051, 2007.

  33. Understanding Internal and External Validity. https://www.verywellmind.com/internal-and-external-validity-4584479#similarities-and-differences. Accessed 09 October 2019.

  34. Snowball Sampling. https://research-methodology.net/sampling-in-primary-data-collection/snowball-sampling/. Accessed 10 October 2019.

  35. Working with percentages. https://www2.le.ac.uk/offices/ld/resources/study-guides-pdfs/numeracy-skillspdfs/Working%20with%20percentages.pdf. Accessed 20 January 2020.

  36. I. Altaf, M. A. Saleem, K. Mahmood, S. Kumari, P. Chaudhary and C. M. Chen, A lightweight key agreement and authentication scheme for satellite-communication systems, IEEE Access, Vol. 8, pp. 46278–46287, 2020.

    Google Scholar 

  37. K. Mahmood, J. Arshad, S. A. Chaudhry and S. Kumari, An enhanced anonymous identity-based key agreement protocol for smart grid advanced metering infrastructure, International Journal of Communication Systems, Vol. 32, No. 16, p. e4137, 2019.

    Google Scholar 

  38. K. Mahmood, H. Naqvi, B. A. Alzahrani, Z. Mehmood, A. Irshad and S. A. Chaudhry, An ameliorated two-factor anonymous key exchange authentication protocol for mobile client-server environment, International Journal of Communication Systems, Vol. 31, No. 18, p. e3814, 2018.

    Google Scholar 

  39. S. Kumari and K. Renuka, A provably secure biometrics and ECC-based authentication and key agreement scheme for WSNs, International Journal of Communication Systems, Vol. 33, No. 3, p. e4194, 2020.

    Google Scholar 

  40. M. A. Saleem, K. Mahmood and S. Kumari, Comment on AKM-IoV: authenticated key management protocol in fog computing-based internet of vehicles deployment, IEEE Internet of Things Journal, 2020.

  41. A. Irshad, S. A. Chaudhry, S. Kumari, M. Usman, K. Mahmood and M. S. Faisal, An improved lightweight multiserver authentication scheme, International Journal of Communication Systems, Vol. 30, No. 17, p. e3351, 2017.

    Google Scholar 

  42. Internal vs external validity. https://www.scribbr.com/methodology/internal-vs-external-validity/. Accessed 22 March 2020.

Download references

Author information

Authors and Affiliations

  1. Department of Information Technology, Babasaheb Bhimrao Ambedkar University (A Central University), Lucknow, UP, India

    Jasleen Kaur, Alka Agrawal & Raees Ahmad Khan

Authors
  1. Jasleen Kaur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alka Agrawal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Raees Ahmad Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

(1) JK made substantial contributions to the design of the work and drafted it. (2) AA revised it critically for important intellectual content; (3) RAK approved the version to be published; and (4) All the authors agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The idea for this review article was based on the discussion among all the three authors. The first author performed the literature search and data analysis. Finally, all the authors critically revised the work prior to submission for publication.

Corresponding author

Correspondence to Jasleen Kaur.

Ethics declarations

Conflict of interest

The authors declare that they have 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

Kaur, J., Agrawal, A. & Khan, R.A. Security Issues in Fog Environment: A Systematic Literature Review. Int J Wireless Inf Networks 27, 467–483 (2020). https://doi.org/10.1007/s10776-020-00491-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10776-020-00491-7

Keywords

Search

Navigation