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Research Article |

Deep Learning based Effective Watermarking Technique for IoT Systems Signal Authentication

Author(s): Dr. Manish Korde*, Dr. Vinit Gupta, Dr. Aditya Mandloi, Dr. Sachin Puntambekar and Devendra Singh Bais

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 12, Issue 1

Publisher : FOREX Publication

Published : 05 February 2024

e-ISSN : 2347-470X

Page(s) : 54-59

DOI: https://doi.org/10.37391/IJEER.120109

Abstract

In order to identify cyber-attacks, this research suggests a special watermarking technique for dynamic IoT System signal validation. IoT Systems (IoTSs) can extract a group of randomly generated characteristics from their produced signal and then periodically watermark these attributes into the transmission owing to the proposed efficient watermarking technique. Using dynamic watermarking for IoT signal authentication, a potent deep learning technique is used to detect cyber-attacks. Based on an LSTM structure, the proposed learning system enables IoT devices to extract a set of random features from the signal they release, hence enabling dynamic watermarking of the signal.

Keywords: Long Short-Term Memory, IoT System, Dynamic Watermarking, Deep Reinforcement Learning, Signal Authentication.




Dr. Manish Korde*, Assistant Professor, Department of Electronics and Communication Engineering, Medi-Caps University, Indore, Madhya Pradesh, India; Email: manish.korde@medicaps.ac.in

Dr. Vinit Gupta, Assistant Professor, Department of Electronics and Communication Engineering, Medi-Caps University, Indore, Madhya Pradesh, India; Email: vinit@medicaps.ac.in

Dr. Aditya Mandloi, Assistant Professor, Department of Electronics and Communication Engineering, Medi-Caps University, Indore, Madhya Pradesh, India; Email: aditya.mandloi@medicaps.ac.in

Dr. Sachin Puntambekar, Assistant Professor, Department of Electronics and Communication Engineering, Medi-Caps University, Indore, Madhya Pradesh, India; Email: sachin.puntambekar@medicaps.ac.in

Devendra Singh Bais, Assistant Professor, Department of Electronics and Communication Engineering, Medi-Caps University, Indore, Madhya Pradesh, India; Email: devendrasingh.bais@medicaps.ac.in

    [1] A. Ferdowsi, and W. Saad (2018, May). Deep learning-based dynamic watermarking for secure signal authentication in the Internet of Things. In 2018 IEEE International Conference on Communications, pp. 1-6. [CrossRef]
    [2] S. Ali, N. Rajatheva, and W. Saad (2019), Fast uplink grant for machine type communications: Challenges and opportunities. IEEE Communications Magazine, Vol. 57, No. 3, pp. 97-103. [CrossRef]
    [3] P. Sethi, and S. R. Sarangi (2017), Internet of things: architectures, protocols, and applications. Journal of Electrical and Computer Engineering, 2017. [CrossRef]
    [4] Latvala, S., Sethi, M., & Aura, T. (2020). Evaluation of out-of-band channels for IoT security. SN Computer Science, Vol. 1, pp. 1-17. [CrossRef]
    [5] D. U. Ugli Jurayev, (2022), Security in the Internet of Things: A Review. Texas Journal of Engineering and Technology, Vol. 11, pp. 15-17.
    [6] R. Wazirali, R. Ahmad, A. Al-Amayreh, M. Al-Madi, and A. Khalifeh, (2021). Secure watermarking schemes and their approaches in the IoT technology: an overview. Electronics, Vol. 10, No. 14, pp. 1744. [CrossRef]
    [7] A. Mukherjee (2015). Physical-layer security in the Internet of Things: Sensing and communication confidentiality under resource constraints. Proceedings of the IEEE, Vol. 103, No.10, pp. 1747-1761. [CrossRef]
    [8] W. Trappe (2015), The challenges facing physical layer security. IEEE communications magazine, Vol. 53, No. 6, pp. 16-20. [CrossRef]
    [9] J. Y. Lee, W. C. Lin, and Y. H. Huang, (2014, May). A lightweight authentication protocol for internet of things. In 2014 International Symposium on Next-Generation Electronics (ISNEI), pp. 1-2. [CrossRef]
    [10] P. N. Mahalle, B. Anggorojati, N. R. Prasad, and R. Prasad (2013). Identity authentication and capability-based access control (iacac) for the internet of things. Journal of Cyber Security and Mobility, Vol. 1, No. 4, pp. 309-348. [CrossRef]
    [11] P. Hespanhol, M. Porter, R. Vasudevan, and A. Aswani, A (2017, December). Dynamic watermarking for general LTI systems. In 2017 IEEE 56th Annual Conference on Decision and Control (CDC), pp. 1834-1839. [CrossRef]
    [12] M. Hosseini, T. Tanaka, and V. Gupta (2016, June). Designing optimal watermark signal for a stealthy attacker. In 2016 European Control Conference (ECC), pp. 2258-2262. IEEE. [CrossRef]
    [13] B. Satchidanandan, and P. R Kumar (2016). Dynamic watermarking: Active defense of networked cyber–physical systems. Proceedings of the IEEE, Vol. 105, No. 2, pp. 219-240.
    [14] M. Porter, P. Hespanhol, A. Aswani, M. Johnson-Roberson, and R. Vasudevan, (2020). Detecting generalized replay attacks via time-varying dynamic watermarking. IEEE Transactions on Automatic Control, Vol. 66, No. 8, pp. 3502-3517. [CrossRef]
    [15] C. M. Ahmed, V.R. Palleti and V. K. Mishra, (2022). A practical physical watermarking approach to detect replay attacks in a CPS. Journal of Process Control, Vol. 116, pp. 136-146. [CrossRef]
    [16] W. Chen, X. Qiu, T. Cai, H.N. Dai, Z. Zheng and Y. Zhang, (2021). Deep reinforcement learning for Internet of Things: A comprehensive survey. IEEE Communications Surveys & Tutorials, Vol. 23, no. 3, pp. 1659-1692. [CrossRef]
    [17] M. A. Jan, F. Khan, S. Mastorakis, M. Adil, A. Akbar and N. Stergiou, (2021). LightIoT: Lightweight and secure communication for energy-efficient IoT in health informatics. IEEE transactions on green communications and networking, vol. 5, no. 3, pp. 1202-1211. [CrossRef]

Dr. Manish Korde, Dr. Vinit Gupta, Dr. Aditya Mandloi, Dr. Sachin Puntambekar, Devendra Singh Bais (2024), Deep Learning based Effective Watermarking Technique for IoT Systems Signal Authentication. IJEER 12(1), 54-59. DOI: 10.37391/IJEER.120109.