An Efficient Authentication for IoT Devices Using Fuzzy Trust Privacy-Preserving Scheme

International Journal of Electronics and Communication Engineering
© 2024 by SSRG - IJECE Journal
Volume 11 Issue 10
Year of Publication : 2024
Authors : T. Yuvarani, A. R. Arunachalam
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How to Cite?

T. Yuvarani, A. R. Arunachalam, "An Efficient Authentication for IoT Devices Using Fuzzy Trust Privacy-Preserving Scheme," SSRG International Journal of Electronics and Communication Engineering, vol. 11,  no. 10, pp. 258-265, 2024. Crossref, https://doi.org/10.14445/23488549/IJECE-V11I10P121

Abstract:

The Internet of Things (IoT) improves everyday life by expanding interactions among gadgets. The spike in the assortment of gadgets connected exposes network infrastructure to a variety of dangers. IoT is widely used in the retail, business, manufacturing, construction and defence sectors. Concerns about protecting information and authentication of identities are becoming more and more important as applications for the IoT proliferate. The researchers faced additional challenges in implementing security systems in IoT networks due to resource constraints on sensor nodes. To help prevent such assaults, some expensive Privacy-Preserving (PP) techniques have been used in past research. To manage resource usage alongside information security problems, a unique Fuzzy Trust Privacy-Preserving Scheme (FTPPS) is presented for the IoT context. When the packet length exceeds 400, and the overall number of repetitions is 100, then the suggested FTPPS takes less than 1 second to execute. The recommended FTPPS approach achieves 98 percent trust. Safety and reliability studies demonstrate that our suggested approach is not only resistant to a variety of assaults but also extremely effective with respect to computational efficiency.

Keywords:

Authentication, IoT, Privacy-preserving, Fuzzy trust, Attacks.

References:

[1] Alexander Yohan, and Nai-Wei Lo, “FOTB: A Secure Blockchain-Based Firmware Update Framework for IoT Environment,” International Journal of Information Security, vol. 19, pp. 257-278, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[2] S.K. Sathya Lakshmi Preeth et al., “An Adaptive Fuzzy Rule Based Energy Efficient Clustering and Immune-Inspired Routing Protocol for WSN assisted IoT System,” Journal of Ambient Intelligence and Humanized Computing, pp. 1-13, 2018. [CrossRef] [Google Scholar] [Publisher Link]
[3] Peiying Zhang et al., “A Security and Privacy-Preserving Approach Based on Data Disturbance for Collaborative Edge Computing in Social IoT Systems,” IEEE Transactions on Computational Social Systems, vol. 9, no. 1, pp. 97-108, 2022. [CrossRef] [Google Scholar] [Publisher Link]
[4] Laicheng Cao, and Min Zhu, “Fuzzy-Based Privacy-Preserving Scheme of Low Consumption and High Effectiveness for IoTs: A Repeated Game Model,” Sensors, vol. 22, no. 15, pp. 1-16, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Alawi A. Al-saggaf et al., “Lightweight Two-Factor-Based User Authentication Protocol for IoT-Enabled Healthcare Ecosystem in Quantum Computing,” Arabian Journal for Science and Engineering, vol. 48, pp. 2347-2357, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[6] N. Jyothi, and Rekha Patil, “A Fuzzy-Based Trust Evaluation Framework for Efficient Privacy Preservation and Secure Authentication in VANET,” Journal of Information and Telecommunication, vol. 6, no. 3, pp. 270-288, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Alaa Omran Almagrabi, and A.K. Bashir, “A Classification-Based Privacy-Preserving Decision-Making for Secure Data Sharing in IoT Assisted Applications,” Digital Communications and Networks, vol. 8, no. 4, pp. 436-445, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Ping Guo, Wenfeng Liang, and Shuilong Xu, “A Privacy Preserving Four-Factor Authentication Protocol for Internet of Medical Things,” Computers & Security, vol. 137, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Jiannan Wei, Tran Viet Xuan Phuong, and Guomin Yang, “An Efficient Privacy Preserving Message Authentication Scheme for Internet-of-Things,” IEEE Transactions on Industrial Informatics, vol. 17, no. 1, pp. 617-626, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Prosanta Gope, and Biplab Sikdar, “Lightweight and Privacy-Preserving Two-Factor Authentication Scheme for IoT Devices,” IEEE Internet of Things Journal, vol. 6, no. 1, pp. 580-589, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Xiong Li et al., “A Three-Factor Anonymous Authentication Scheme for Wireless Sensor Networks in Internet of Things Environments,” Journal of Network and Computer Applications, vol. 104, pp. 194-204, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Jiancheng Chi et al., “A Secure and Efficient Data Sharing Scheme based on Blockchain in Industrial Internet of Things,” Journal of Network and Computer Applications, vol. 167, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Gautam Srivastava et al., “Data Sharing and Privacy for Patient IoT Devices using Blockchain,” Smart City and Informatization, Communications in Computer and Information Science, pp. 334-348, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Qing Fan et al., “A Secure and Efficient Authentication and Data Sharing Scheme for Internet of Things based on Blockchain,” Journal of Systems Architecture, vol. 117, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Hanshu Hong, Bing Hu, and Zhixin Sun, “Toward Secure and Accountable Data Transmission in Narrow Band Internet of Things Based on Blockchain,” International Journal of Distributed Sensor Networks, vol. 15, no. 4, pp. 1-10, 2019. [CrossRef] [Google Scholar] [Publisher Link]
[16] Boddupalli Anvesh Kumar, and V. Bapuji, “Efficient Privacy Preserving Communication Protocol for IOT Applications,” Brazilian Journal of Development, vol. 10, no. 1, pp. 402-419, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Nouredine Tamani, and Yacine Ghamri-Doudane, “Towards a User Privacy Preservation System for IoT Environments: A Habit-Based Approach,” 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Vancouver, BC, Canada, pp. 2425-2432, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Inayat Ali, Eraj Khan, and Sonia Sabir, “Privacy-Preserving Data Aggregation in Resource-Constrained Sensor Nodes in Internet of Things: A Review,” Future Computing and Informatics Journal, vol. 3, no. 1, pp. 41-50, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Yuzhe Li, Ling Shi, and Tongwen Chen, “Detection Against Linear Deception Attacks on Multi-Sensor Remote State Estimation,” IEEE Transactions on Control of Network Systems, vol. 5, no. 3, pp. 846-856, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Chunyang Qi et al., “A Novel Privacy-Preserving Mobile-Coverage Scheme Based on Trustworthiness in HWSNs,” Wireless Communications and Mobile Computing, vol. 2021, no. 1, pp. 1-11, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Dan Boneh et al., “Signing a Linear Subspace: Signature Schemes for Network Coding,” Proceedings of the International Workshop on Public Key Cryptography, Irvine, CA, USA, pp. 68-87, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Qun Lin et al., “An ID-Based Linearly Homomorphic Signature Scheme and its Application in Blockchain,” IEEE Access, vol. 6, pp. 20632-20640, 2018.
[CrossRef] [Google Scholar] [Publisher Link]