Architecture and iot security systems based on fog computing

Authors

DOI:

https://doi.org/10.30837/ITSSI.2024.27.054

Keywords:

cloud; fog computing; architecture; Internet of Things; IoT security.

Abstract

The subject of the study is is the security architecture of the Internet of Things (IoT) based on fog computing, which allows providing efficient and secure services for many IoT users. The goal is to investigate the security architecture for IoT systems based on fog computing. To achieve the goal, the following tasks were solved: the concept of fog computing is proposed, its architecture is considered and a comparative analysis of fog and cloud computing architectures is made; the principles of designing and implementing the architecture of a fog computing system are outlined; multi-level security measures based on fog computing are investigated; and the areas of use of fog computing-based Internet of Things networks are described. When performing the tasks, such research methods were used as: theoretical analysis of literature sources; analysis of the principles of designing and implementing the security architecture of the Internet of Things; analysis of security measures at different levels of the architecture. The following results were obtained: the architecture of fog computing is considered and compared with the cloud architecture; the principles of designing and implementing the architecture of fog computing systems are formulated; multi-level IoT security measures based on fog computing are proposed. Conclusions: research on IoT security systems based on fog computing has important theoretical implications. The fog computing architecture, in contrast to the cloud architecture, better meets the demand for high traffic and low latency of mobile applications, providing more advantages for systems that require real-time information processing. When designing and implementing the architecture of fog computing systems, the factors of memory capacity, latency, and utility should be taken into account to effectively integrate fog technologies with IoT. To ensure a high level of system security, multi-level security measures should be implemented using both software and hardware solutions.

Author Biographies

Oleh Zhurylo, Kharkiv National University of Radio Electronics

Postgraduate Student at the Department of Information Technology Security, Assistant Lecturer at the Department of Electronic Computers

Oleksii Liashenko, Kharkiv National University of Radio Electronics

PhD (Engineering Sciences), Associate Professor, Associate Professor at the Department of Electronic Computers

References

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References

Kartheek, D., Bhushan, Bharath. (2020), "Security Issues in Fog Computing for Internet of Things", Security Issues in Fog Computing for Internet of Things. 11 р. DOI: https://doi.org/10.4018/978-1-7998-0194-8.ch003

Atlam, H., Walters, R., Wills, G. (2018), "Fog computing and the Internet of Things: a review". Big Data Cogn Comput. Vol. 2(2): 10. DOI: https://www.mdpi.com/2504-2289/2/2/10

Alrawais, A., Alhothaily, A., Hu, C. (2017), "Fog computing for the Internet of Things: security and privacy issues". IEEE Internet Comput 21(2), P. 34–42. DOI: https://ieeexplore.ieee.org/document/7867732

Thota, C., Sundarasekar, R., Manogaran, G. (2018), "Centralized fog computing security platform for IoT and cloud in healthcare system". Fog computing: breakthroughs in research and practice, P. 365–378. DOI: https://doi.org/10.4018/978-1-5225-5649-7.ch018

Zhang, P.Y., Zhou, M.C., Fortino, G. (2018), "Security and trust issues in fog computing: a survey". Future Generation Computer Systems, 88, P. 16–27. DOI: https://doi.org/10.1016/j.future.2018.05.008

Wen, Z., Yang, R., Garraghan, P. (2018), "Fog orchestration for Internet of Things services". IEEE Internet Computing, 21(2), P. 16–24. DOI: https://ieeexplore.ieee.org/document/7867735

Oleh, Zhurylo, Oleksii, Liashenko, Karyna, Avetisova. (2023), "Hardware security overview of fog computing end devices in the internet of things", Innovative Technologies and Scientific Solutions for Industries, No. 1 (23), P. 5–15. DOI: https://doi.org/10.30837/ITSSI.2023.23.005

Liu, F., Liu, Y., Jin, D., Jia, X., & Wang, T. (2018), "Research on workshop-based positioning technology based on internet of things in big data background", Complexity Problems Handled by Big Data Technology. Р. 1–12. DOI: https://doi.org/10.1155/2018/7875460

S. Shen, L. Huang, H. Zhou, S. Yu, E. Fan and Q. Cao. (2018), "Multistage Signaling Game-Based Optimal Detection Strategies for Suppressing Malware Diffusion in Fog-Cloud-Based IoT Networks," IEEE Internet of Things Journal, 2, P. 1043–1054. DOI: https://ieeexplore.ieee.org/document/8264678

Mulfari, D., Celesti, A., & Villari, M. (2015), "A computer system architecture providing a user-friendly man machine interface for accessing assistive technology in cloud computing". Journal of Systems and Software, P. 129–138. DOI: https://doi.org/10.1016/j.jss.2014.10.035

Wang, D., Fan, J., Fu, H., & Zhang, B. (2018), "Research on optimization of big data construction engineering quality management based on RNN-LSTM", Complexity Problems Handled by Big Data Technology. Р. 1–17. DOI: https://doi.org/10.1155/2018/9691868

Sharma, P. K., Chen, M. Y., & Park, J. H. (2017), "A software defined fog node based distributed blockchain cloud architecture for IoT", IEEE Access, 6, P. 115–124. DOI: https://ieeexplore.ieee.org/document/8053750

Massonet, P., Deru, L., Achour, A., Dupont, S., Croisez, L. M., Levin, A., & Villari, M. (2017), "Security in lightweight network function virtualisation for federated cloud and IoT", 2017 IEEE 5th International Conference on Future Internet of Things and Cloud (FiCloud). P. 148–154. DOI: https://ieeexplore.ieee.org/abstract/document/8114476

Li, G., Wu, J., Li, J., Wang, K., & Ye, T. (2018), "Service popularity-based smart resources partitioning for fog computing-enabled industrial Internet of Things", IEEE Transactions on Industrial Informatics, 14, P. 4702–4711. DOI: https://ieeexplore.ieee.org/abstract/document/8377998

Aimin, Y., Shanshan, L., Honglei, L., & Donghao, J. (2018), "Edge extraction of mineralogical phase based on fractal theory", Chaos, Solitons & Fractals, 117. P. 215–221. DOI: https://doi.org/10.1016/j.chaos.2018.09.028

R. Yaroshevych, V. Tkachov, A. Kovalenko and D. Rosinskyi (2022), "Modelling the Domain Architecture of the Tactile Internet Using a Foggy Infrastructure," 2022 IEEE 9th International Conference on Problems of Infocommunications, Science and Technology (PIC S&T). P. 512–516. DOI: 10.1109/PICST57299.2022.10238653

Dutta, J., & Roy, S. (2017), "IoT-fog-cloud based architecture for smart city: Prototype of a smart building". 2017 7th international conference on cloud computing, data science & engineering-confluenc. P. 237–242. DOI: https://ieeexplore.ieee.org/abstract/document/7943156

Peralta, G., Iglesias-Urkia, M., Barcelo, M., Gomez, R., Moran, A., & Bilbao, J. (2017), "Fog computing based efficient IoT scheme for the Industry 4.0", 2017 IEEE international workshop of electronics, control, measurement, signals and their application to mechatronics (ECMSM). P. 1–6. DOI: https://ieeexplore.ieee.org/abstract/document/7945879

Fu, H., Li, Z., Liu, Z., & Wang, Z. (2018), "Research on big data digging of hot topics about recycled water use on micro-blog based on particle swarm optimization", Sustainability, 10. 2488 р. DOI: https://doi.org/10.3390/su10072488

Ong, S. P., Cholia, S., Jain, A., Brafman, M., Gunter, D., Ceder, G., & Persson, K. A. (2015), "The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles", Computational Materials Science, 97, P. 209–215. DOI: https://doi.org/10.1016/j.commatsci.2014.10.037

Goldstein, S. W. (2018), Information processing using a population of data acquisition devices U.S. Patent No. 10,045,321. available at: https://patents.google.com/patent/US20160309312A1/en

Son, J., & Buyya, R. (2018), "A taxonomy of software-defined networking (SDN)-enabled cloud computing". ACM computing surveys (CSUR), 51. P. 1–36. DOI: https://doi.org/10.1145/3190617

Published

2024-07-02

How to Cite

Zhurylo, O., & Liashenko, O. (2024). Architecture and iot security systems based on fog computing. INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, (1 (27), 54–66. https://doi.org/10.30837/ITSSI.2024.27.054