Education, Science, Technology, Innovation and Life
Open Access
Sign In

Data Security in Industrial IoT: Challenges and Emerging Solutions

Download as PDF

DOI: 10.23977/ieim.2025.080214 | Downloads: 0 | Views: 77

Author(s)

Fei Lu 1, Haojing Huang 1,2, Zhiming Cai 3, Jian Chen 3

Affiliation(s)

1 School of Engineering and Technology, Guangdong Polytechnic Institute, Guangzhou, China
2 Faculty of Data Science, City University of Macau, Macau, China
3 Faculty of Digital Science and Technology, Macau Millennium College, Macau, China

Corresponding Author

Zhiming Cai

ABSTRACT

The implementation of Industrial Internet of Things (IIoT) is significantly constrained by the emergence of Data security. This paper examines the primary data security issues and protection mechanisms associated with IIoT, providing a comprehensive analysis of how security protection systems evolve across the stages of data collection, transmission, storage, and processing. The focus is directed towards advancements in edge computing and lightweight distributed ledger technologies, which significantly enhance data security. The paper begins with a review of the evolution and development of IIoT, highlighting the challenges that current technologies present in effectively addressing data privacy, integrity, real-time performance, and scalability. Following this, the analysis focuses on the efficacy of edge computing to mitigate data exposure while simultaneously improving computational efficiency. Additionally, the study examines the benefits of lightweight distributed ledger technologies for resource-constrained environments, highlighting their role in ensuring data immutability and enhancing data transparency. The paper concludes by analyzing potential trends in IIoT data security technologies, such as post-quantum cryptography, AI-driven security protections, and zero-trust architectures, and by offering perspectives on the future of technological advancements.

KEYWORDS

Industrial Internet of Things, Data Security, Edge Computing, Lightweight Distributed Ledger

CITE THIS PAPER

Fei Lu, Haojing Huang, Zhiming Cai, JianChen, Data Security in Industrial IoT: Challenges and Emerging Solutions. Industrial Engineering and Innovation Management (2025) Vol. 8: 90-103. DOI: http://dx.doi.org/10.23977/ieim.2025.080214.

REFERENCES

[1] SISINNI E, SAIFULLAH A, HAN S, et al. Industrial internet of things: Challenges, opportunities, and directions [J]. IEEE transactions on industrial informatics, 2018, 14(11): 4724-4734.
[2] ULLAH I, ADHIKARI D, SU X, et al. Integration of data science with the intelligent IoT (IIoT): current challenges and future perspectives [J]. Digital Communications and Networks, 2024, 10(1): 1-19.
[3] MYROSHNYK Y. State of IoT Summer 2024 [Z]//MYROSHNYK Y. 2024
[4] 360IRESEARCH. Industrial Internet of Things Market by Component (Hardware, Services, Software), Connectivity (Satellite Connectivity, Wired Connectivity, Wireless Connectivity), End-User—Global Forecast 2025–2030 [Z]. 360iResearch / Global Information, Inc. 2024
[5] MUNIRATHINAM S. Chapter Six - Industry 4.0: Industrial Internet of Things (IIOT) [M]//RAJ P, EVANGELINE P. Advances in Computers. Elsevier. 2020: 129-164.
[6] LUO Q, HU S, LI C, et al. Resource Scheduling in Edge Computing: A Survey [J]. IEEE Communications Surveys & Tutorials, 2021, 23(4): 2131-2165.
[7] ENERGY F M F E A A. German Industrial Strategy 2030: Guidelines for a German and European Industrial Policy [R]. Berlin, 2019.
[8] COMMISSION E. A European Strategy for Data [R]. Brussels, 2020.
[9] IVANOV D. The Industry 5.0 framework: viability-based integration of the resilience, sustainability, and human-centricity perspectives [J]. International Journal of Production Research, 2023, 61(5): 1683-1695.
[10] COELHO P, BESSA C, LANDECK J, et al. Industry 5.0: The Arising of a Concept [J]. Procedia Computer Science, 2023, 217: 1137-1144.
[11] LIN H, JIANJUN Y, SHA W, et al. Construction and Implementation Path for Industrial Internet Standards System in China [J]. Strategic Study of Chinese Academy of Engineering, 2021, 23(2): 88-94.
[12] HOUSE T W. National Cybersecurity Strategy [Z]. The White House, Office of the National Cyber Director. 2023
[13] ABUHASEL K A, KHAN M A. A Secure Industrial Internet of Things (IIoT) Framework for Resource Management in Smart Manufacturing [J]. IEEE Access, 2020, 8(6): 117354-117364.
[14] ZHOU H, XU W, CHEN J, et al. Evolutionary V2X technologies toward the Internet of vehicles: Challenges and opportunities [J]. Proceedings of the IEEE, 2020, 108(2): 308-323.
[15] PU C, WALL A, CHOO K K R, et al. A Lightweight and Privacy-Preserving Mutual Authentication and Key Agreement Protocol for Internet of Drones Environment [J]. IEEE Internet of Things Journal, 2022, 9(12): 9918-9933.
[16] HUO R, ZENG S, WANG Z, et al. A Comprehensive Survey on Blockchain in Industrial Internet of Things: Motivations, Research Progresses, and Future Challenges [J]. IEEE Communications Surveys & Tutorials, 2022, 24(1): 88-122.
[17] YANG H, BAO B, LI C, et al. Blockchain-enabled tripartite anonymous identification trusted service provisioning in industrial IoT [J]. IEEE Internet of Things Journal, 2021, 9(3): 2419-2431.
[18] YIN D, GONG B. A Lightweight Certificateless Mutual Authentication Scheme Based on Signatures for IIoT [J]. IEEE Internet of Things Journal, 2024, 11(16): 26852-26865.
[19] CASTIGLIONE A, NAPPI M, RICCIARDI S. Trustworthy method for person identification in IIoT environments by means of facial dynamics [J]. IEEE Transactions on Industrial Informatics, 2020, 17(2): 766-774.
[20] ZHANG Z, HUANG W, HUANG Y, et al. A Domain Isolated Tripartite Authenticated Key Agreement Protocol With Dynamic Revocation and Online Public Identity Updating for IIoT [J]. IEEE Internet of Things Journal, 2024, 11(9): 15616-15632.
[21] ZHU W, CHEN X, JIANG L. A secure and efficient authentication key agreement scheme for industrial internet of things based on edge computing [J]. Alexandria Engineering Journal, 2024, 101: 52-61.
[22] KOPROV P, FANG X, STARLY B. Machine identity authentication via unobservable fingerprinting signature: A functional data analysis approach for MQTT 5.0 protocol [J]. Journal of Manufacturing Systems, 2024, 76: 59-74.
[23] AHMED S F, SHAWON S S, BHUYIAN A, et al. Forensics and security issues in the Internet of Things [J]. Wireless Networks, 2025, 31(4): 3431-3466.
[24] HASAN M K, WEICHEN Z, SAFIE N, et al. A survey on key agreement and authentication protocol for internet of things application [J]. IEEE access, 2024, 12(4): 61642-61666.
[25] MICHAELIDES S, LENZ S, VOGT T, et al. Secure integration of 5G in industrial networks: State of the art, challenges and opportunities [J]. Future Generation Computer Systems, 2024: 107645.
[26] RUOTSALAINEN H, SHEN G, ZHANG J, et al. LoRaWAN Physical Layer-Based Attacks and Countermeasures, A Review [J]. Sensors, 2022, 22(9): Article NO. 3127.
[27] ALOTAIBI B. A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-Based Solutions, and Edge Computing Opportunities [J]. Sensors, 2023, 23(17): Article NO. 7470.
[28] FORUM W E, ACCENTURE. Global Cybersecurity Outlook 2025 [Z]//FORUM W E. World Economic Forum. 2025
[29] ROTH E. Volkswagen leak exposed location data for 800,000 electric cars [Z]//ROTH E. 2024
[30] INSIGHTS D. From "hindsight" to "foresight" - releasing the value of the Internet of Things industrial field [Z]//INSIGHTS D. Deloitte. 2023
[31] WANG X, HAN Y, LEUNG V C M, et al. Convergence of Edge Computing and Deep Learning: A Comprehensive Survey [J]. IEEE Communications Surveys & Tutorials, 2020, 22(2): 869-904.
[32] ZHOU Z, CHEN X, LI E, et al. Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing [J]. Proceedings of the IEEE, 2019, 107(8): 1738-1762.
[33] LIU L, FENG J, MU X, et al. Asynchronous Deep Reinforcement Learning for Collaborative Task Computing and On-Demand Resource Allocation in Vehicular Edge Computing [J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(12): 15513-15526.
[34] NGUYEN D C, DING M, PHAM Q V, et al. Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challenges [J]. IEEE Internet of Things Journal, 2021, 8(16): 12806-12825.
[35] M P, BOUROUIS S, AHMED A N, et al. A Novel Secured Multi-Access Edge Computing based VANET with Neuro fuzzy systems based Blockchain Framework [J]. Computer Communications, 2022, 192(8): 48-56.
[36] HARTMANN M, HASHMI U S, IMRAN A. Edge computing in smart health care systems: Review, challenges, and research directions [J]. Transactions on Emerging Telecommunications Technologies, 2022, 33(3): e3710.
[37] GUO J, CHEN H, SONG B, et al. Distributed Task-Oriented Communication Networks with Multimodal Semantic Relay and Edge Intelligence [J]. IEEE Communications Magazine, 2024, 62(6): 82-89.
[38] HUA H, LI Y, WANG T, et al. Edge Computing with Artificial Intelligence: A Machine Learning Perspective [J]. ACM Comput Surv, 2023, 55(9): Article NO. 184.
[39] ZSCALER. Zscaler Finds Over 87% of Cyberthreats Hide in Encrypted Traffic, Reinforcing the Need for Zero Trust [Z]. web; Zscaler. 2024
[40] GUO F, XIAO X, HECKER A, et al. A theoretical model characterizing tangle evolution in IOTA blockchain network [J]. IEEE Internet of Things Journal, 2022, 10(2): 1259-1273.
[41] ZHANG C, ZHAO M, LIANG J, et al. Nano: Cryptographic enforcement of readability and editability governance in blockchain databases [J]. IEEE Transactions on Dependable and Secure Computing, 2023, 21(4): 3439-3452.
[42] WOZNICA A, KEDZIORA M. Performance and scalability evaluation of a permissioned Blockchain based on the Hyperledger Fabric, Sawtooth and Iroha [J]. Computer Science and Information Systems, 2022, 19(2): 659-678.
[43] QURESHI M U, GRAUX D, ORLANDI F, et al. Auto-generation of blockchain-based distributed applications using ontologies [M]. Blockchain and Smart-Contract Technologies for Innovative Applications. Springer. 2024: 217-258.
[44] MAZZONI M, CORRADI A, DI NICOLA V. Performance evaluation of permissioned blockchains for financial applications: The ConsenSys Quorum case study [J]. Blockchain: Research and applications, 2022, 3(1): Article NO.100026.
[45] JNR B A, SYLVA W, WATAT J K, et al. A framework for standardization of distributed ledger technologies for interoperable data integration and alignment in sustainable smart cities [J]. Journal of the Knowledge Economy, 2024, 15(3): 12053-12096.
[46] HUANG Z, WANG H, CAO B, et al. A comprehensive side-channel leakage assessment of CRYSTALS-Kyber in IIoT [J]. Internet of Things, 2024, 27: Article NO. 101331.
[47] XIONG J, SHEN L, LIU Y, et al. Enhancing IoT security in smart grids with quantum-resistant hybrid encryption [J]. Scientific Reports, 2025, 15(1): Article NO. 3 (2025).
[48] CASTIGLIONE A, ESPOSITO J G, LOIA V, et al. Integrating Post-Quantum Cryptography and Blockchain to Secure Low-Cost IoT Devices [J]. IEEE Transactions on Industrial Informatics, 2024, 21(2): 1-10.
[49] QUY V K, NGUYEN D C, VAN ANH D, et al. Federated learning for green and sustainable 6G IIoT applications [J]. Internet of Things, 2024, 25: Article NO. 101061.
[50] KARACAYıLMAZ G, ARTUNER H. A novel approach detection for IIoT attacks via artificial intelligence [J]. Cluster Computing, 2024, 27(6): 10467-10485.
[51] SHOUKAT S, GAO T, JAVEED D, et al. Trust my IDS: An explainable AI integrated deep learning-based transparent threat detection system for industrial networks [J]. Computers & Security, 2025, 149: Article NO. 104191.
[52] DING X, WANG J, ZHAO Y, et al. Lightweight batch authentication and key agreement scheme for IIoT gateways [J]. Journal of Systems Architecture, 2025: 103368.
[53] ZHUANG C, DAI Q, ZHANG Y. A secure and lightweight data management scheme based on redactable blockchain for Digital Copyright [J]. Computer Standards & Interfaces, 2025, 91(3): Article NO. 103875.
[54] MEHMOOD F, KHAN A A, WANG H, et al. BLPCA-ledger: A lightweight plenum consensus protocols for consortium blockchain based on the hyperledger indy [J]. Computer Standards & Interfaces, 2025, 91(3): Article NO. 103876.
[55] ZANASI C, RUSSO S, COLAJANNI M. Flexible zero trust architecture for the cybersecurity of industrial IoT infrastructures [J]. Ad Hoc Networks, 2024, 156(12): Article NO. 103414.
[56] SINGH A, DHANARAJ R K, SHARMA A K. Personalized device authentication scheme using Q-learning-based decision-making with the aid of transfer fuzzy learning for IIoT devices in zero trust network (PDA-QLTFL) [J]. Computers and Electrical Engineering, 2024, 118(3): Article NO. 109435.
[57] ALEISA M A. Blockchain-Enabled Zero Trust Architecture for Privacy-Preserving Cybersecurity in IoT Environments [J]. IEEE Access, 2025, 13(1): 18660 - 18676.

Downloads: 25872
Visits: 737051

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.