Skip to main content

Advertisement

Log in

Secure energy aware routing protocol for trust management using enhanced Dempster Shafer evidence model in multi-hop UWAN

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

At present, underwater wireless ad hoc networks (UWAN) are widely used in enormous applications. At the same time, UWAN faced many security issues, like energy leaks. The energy hole will make the network lifetime end soon. However, most existing underwater research has not taken security as serious threat. This article aims to provide a new secure data transmission scheme in UWAN, in which the management and deployment of UWAN is typically done by a trusted authority. The proposed Cluster Tree Enhanced Dempster Shafer based Bidirectional Butterfly Optimization algorithm (CT-EDS-BBO) will be divided into three phases. Initially, the cluster-based tree routing protocol designed for cluster formation, CH selection process, and routing process establishment. In the second phase, the Enhanced Dempster Shafer Evidence Theory uses the fusion rule to evaluate the trust value for each node, which is used to determine the security of each node and to detect the Malicious Node. Finally, the Bidirectional Butterfly Optimization algorithm model is designed to avoid the energy hole issue and to allocate a routing channel for secure data transmission over UWAN. The results obtained from simulation analysis demonstrate that the proposed CT-EDS-BBO has observable benefits over the conventional methods with a Packet Delivery Ratio of 90%, energy consumption of 0.14 J, a network lifetime of 732 s for 200 rounds, and an end-to-end delay of 0.12 s.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Kuzminykh, I., Carlsson, A., Yevdokymenko, M., & Sokolov, V. (2019). Investigation of the IoT device lifetime with secure data transmission. In O. Galinina, S. Andreev, S. Balandin, & Y. Koucheryavy (Eds.), Internet of things, smart spaces, and next generation networks and systems (pp. 16–27). Cham: Springer.

    Chapter  Google Scholar 

  2. Elhoseny, M., & Shankar, K. (2019). Reliable data transmission model for mobile ad hoc network using signcryption technique. IEEE Transactions on Reliability, 69(3), 1077–1086.

    Article  Google Scholar 

  3. Han, G., He, Y., Jiang, J., Wang, N., Guizani, M., & Ansere, J. A. (2019). A synergetic trust model based on SVM in underwater acoustic sensor networks. IEEE Transactions on Vehicular Technology, 68(11), 11239–11247.

    Article  Google Scholar 

  4. Babaeer, H. A., & Al-Ahmadi, S. A. (2020). Efficient and secure data transmission and sinkhole detection in a multi-clustering wireless sensor network based on homomorphic encryption and watermarking. IEEE Access, 8, 92098–92109.

    Google Scholar 

  5. Gomathi, R. M., & Manickam, J. M. L. (2019). Energy efficient static node selection in underwater acoustic wireless sensor network. Wireless Personal Communications, 107(2), 709–727.

    Article  Google Scholar 

  6. Yang, G., Dai, L., Si, G., Wang, S., & Wang, S. (2019). Challenges and security issues in underwater wireless sensor networks. Procedia Computer Science, 147, 210–216.

    Article  Google Scholar 

  7. Rao, P. V., Varma, N. M. K., & Sudhakar, R. (2020). A systematic survey on software-defined networks, routing protocols and security infrastructure for underwater wireless sensor networks (UWSNs). In P. Krishna & M. S. Obaidat (Eds.), emerging research in data engineering systems and computer communications (pp. 551–559). Singapore: Springer.

    Google Scholar 

  8. Sun, S., Chen, D., Liu, N., Huang, X., & Yang, Q. (2021). Energy-saving and efficient underwater wireless sensor network security data aggregation model. In J. MacIntyre, J. Zhao, & X. Ma (Eds.), International conference on machine learning and big data analytics for IoT security and privacy (pp. 211–216). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-62746-1_31

    Chapter  Google Scholar 

  9. Mathapati, M., Kumaran, T. S., Muruganandham, A., & Mathivanan, M. (2021). Secure routing scheme with multi-dimensional trust evaluation for wireless sensor network. Journal of Ambient Intelligence and Humanized Computing, 12(6), 6047–6055.

    Article  Google Scholar 

  10. Guan, Q., Ji, F., Liu, Y., Yu, H., & Chen, W. (2019). Distance-vector-based opportunistic routing for underwater acoustic sensor networks. IEEE Internet of Things Journal, 6(2), 3831–3839.

    Article  Google Scholar 

  11. Sharma, T. K., Sahoo, A. K., & Goyal, P. (2021). Bidirectional butterfly optimization algorithm and engineering applications. Materials Today: Proceedings, 34, 736–741.

    Google Scholar 

  12. Dattatraya, K. N., & Rao, K. R. (2019). Hybrid based cluster head selection for maximizing network lifetime and energy efficiency in WSN. Journal of King Saud University-Computer and Information Sciences. https://doi.org/10.1016/j.jksuci.2019.04.003

    Article  Google Scholar 

  13. Shobana, M., Sabitha, R., & Karthik, S. (2021). Cluster-based systematic data aggregation model (CSDAM) for real-time data processing in large-scale WSN. Wireless Personal Communications, 117(4), 2865–2883.

    Article  Google Scholar 

  14. Jiang, J., Zhu, X., Han, G., Guizani, M., & Shu, L. (2020). A dynamic trust evaluation and update mechanism based on C4. 5 decision tree in underwater wireless sensor networks. IEEE Transactions on Vehicular Technology, 69(8), 9031–9040.

    Article  Google Scholar 

  15. Su, Y., Mal, S., Jin, Z., Fu, X., Li, Y., & Liu, X. (2020, October). A trust model for underwater acoustic sensor networks based on fast link quality assessment. In Global Oceans 2020: Singapore–US Gulf Coast , IEEE 1–6.

  16. Chen, Y., Tang, Y., Fang, X., Wan, L., Tao, Y., & Xu, X. (2021). PB-ACR: Node payload balanced ant colony optimal cooperative routing for multi-hop underwater acoustic sensor networks. IEEE Access, 9, 57165–57178.

    Article  Google Scholar 

  17. Chen, Y., Zhu, J., Wan, L., Huang, S., Zhang, X., & Xu, X. (2020). ACOA-AFSA fusion dynamic coded cooperation routing for different scale multi-hop underwater acoustic sensor networks. IEEE Access, 8, 186773–186788.

    Article  Google Scholar 

  18. Priyadarshini, R. R., & Sivakumar, N. (2020). Relay selection approach in underwater acoustic WSNs using Bi-Partite graph. Wireless Personal Communications, 111(1), 643–660.

    Article  Google Scholar 

  19. Narmeen, R., Ahmad, I., Kaleem, Z., Mughal, U. A., Da Costa, D. B., & Muhaidat, S. (2021). Shortest propagation delay-based relay selection for underwater acoustic sensor networks. IEEE Access, 9, 37923–37935.

    Article  Google Scholar 

  20. Yu, W., Chen, Y., Wan, L., Zhang, X., Zhu, P., & Xu, X. (2020). An energy optimization clustering scheme for multi-hop underwater acoustic cooperative sensor networks. IEEE Access, 8, 89171–89184.

    Article  Google Scholar 

  21. Zhang, M., & Cai, W. (2020). Energy-efficient depth based probabilistic routing within 2-Hop neighborhood for underwater sensor networks. IEEE Sensors Letters, 4(6), 1–4.

    Article  Google Scholar 

  22. Goyal, N., Dave, M., & Verma, A. K. (2020). SAPDA: secure authentication with protected data aggregation scheme for improving QoS in scalable and survivable UWSNs. Wireless Personal Communications, 113(1), 1–15. https://doi.org/10.1007/s11277-020-07175-8

    Article  Google Scholar 

  23. Muthukkumar, R., & Manimegalai, D. (2021). Secured transmission using trust strategy-based dynamic Bayesian game in underwater acoustic sensor networks. Journal of Ambient Intelligence and Humanized Computing, 12(2), 2585–2600.

    Article  Google Scholar 

  24. Wang, J., Qin, Y., Tang, Z., & Zhang, P. (2020). Software-defined cyber-energy secure underwater wireless power transfer. IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 2(1), 21–31.

    Article  Google Scholar 

  25. Zhang, J., Cai, M., Han, G., Qian, Y., & Shu, L. (2020). Cellular clustering-based interference-aware data transmission protocol for underwater acoustic sensor networks. IEEE Transactions on Vehicular Technology, 69(3), 3217–3230.

    Article  Google Scholar 

  26. Jiajia, J., Xianquan, W., Fajie, D., Xiao, F., Chunyue, L., & Zhongbo, S. (2020). A basic bio-inspired camouflage communication frame design and applications for secure underwater communication among military underwater platforms. IEEE Access, 8, 24927–24940.

    Article  Google Scholar 

  27. Guo, Y., Liu, X., & Chen, C. (2019). Research on hybrid cooperative charging scheduling schemes in underwater sensor networks. IEEE Access, 7, 156452–156462.

    Article  Google Scholar 

  28. Kuang, Y., Sun, J., Gan, X., Gong, D., Liu, Z., & Zha, M. (2021). Dynamic multi-objective cooperative coevolutionary scheduling for mobile underwater wireless sensor networks. Computers & Industrial Engineering, 156, 107229.

    Article  Google Scholar 

  29. Su, Y., Zhou, Z., Jin, Z., & Yang, Q. (2020). A joint relay selection and power allocation MAC protocol for underwater acoustic sensor network. IEEE access., 8, 65197–65210.

    Article  Google Scholar 

  30. Khan, A., Javaid, N., Ali, I., Anisi, M. H., Rahman, A. U., Bhatti, N., Zia, M., & Mahmood, H. (2017). An energy efficient interference-aware routing protocol for underwater WSNs. KSII Transactions on Internet and Information Systems, 11(10), 4844–4864.

    Google Scholar 

  31. Ghoreyshi, S. M., Shahrabi, A., Boutaleb, T., & Khalily, M. (2019). Mobile data gathering with hop-constrained clustering in underwater sensor networks. IEEE Access, 7, 21118–21132.

    Article  Google Scholar 

  32. Dini, G., & Lo Duca, A. (2012). A secure communication suite for underwater acoustic sensor networks. Sensors, 12(11), 15133–15158.

    Article  Google Scholar 

  33. Kaliappan, M., & Paramasivan, B. (2015). Enhancing secure routing in mobile ad hoc networks using a dynamic bayesian signalling game model. Computers & Electrical Engineering, 41, 301–313.

    Article  Google Scholar 

Download references

Funding

There is no funding for this study.

Author information

Authors and Affiliations

Authors

Contributions

All the authors have participated in writing the manuscript and have revised the final version. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Surya Narayan Mahapatra.

Ethics declarations

Conflict of interest

Authors declares that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants and/or animals performed by any of the authors.

Informed consent

There is no informed consent for this study.

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

Mahapatra, S.N., Singh, B.K. & Kumar, V. Secure energy aware routing protocol for trust management using enhanced Dempster Shafer evidence model in multi-hop UWAN. Wireless Netw 28, 3059–3076 (2022). https://doi.org/10.1007/s11276-022-03021-w

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-022-03021-w

Keywords

Navigation