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SAPDA: Secure Authentication with Protected Data Aggregation Scheme for Improving QoS in Scalable and Survivable UWSNs

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Abstract

Security is one of the main objectives while designing protocols for underwater wireless sensor networks (UWSN), since the sensors in UWSN are vulnerable to malicious attack. So it becomes easy for opponents to manipulate the communication channel of UWSN and its nodes. Authentication and data integrity play important roles in the context of security to make network scalable and survivable. Hence in this paper, a secure authentication and protected data aggregation method for the cluster based structure of UWSN is proposed as because cluster based arrangement produces a concise and stable network. In this technique, the cluster head in each cluster is authenticated by the gateway to ensure that all the clusters are being handled by valid nodes. Also, the data being communicated in the network will be securely handled to ensure that it will not get compromised during network operations. In this way, the security of all the nodes is ensured to maintain safe network communication. The proposed technique improves the data reliability in the network by reducing the energy consumption and delay. Here, the proposed method is moreover compared with the state of the art techniques to prove the validity and effectiveness.

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References

  1. Yoon, S., & Qiao, C. (2010). Cooperative search and survey using autonomous underwater vehicles (AUVs). IEEE Transactions on Parallel and Distributed Systems,22(3), 364–379.

    Article  Google Scholar 

  2. Goyal, N., Dave, M., & Verma, A. K. (2019). Protocol stack of underwater wireless sensor network: Classical approaches and new trends. Wireless Personal Communications,104(3), 995–1022.

    Article  Google Scholar 

  3. Zandi, R., Kamarei, M., & Amiri, H. (2016). Distributed estimation of sensors position in underwater wireless sensor network. International Journal of Electronics,103(5), 853–867.

    Google Scholar 

  4. Hamilton, E. I., & Minski, M. J. (1972). Comments on the trace element chemistry of water: Sampling a key factor in water quality surveillance. Environmental Letters,3(1), 53–71.

    Article  Google Scholar 

  5. Das, A. P., & Thampi, S. M. (2015). Secure communication in mobile underwater wireless sensor networks. In IEEE international conference on advances in computing, communications and informatics (ICACCI) (pp. 2164–2173).

  6. Han, G., Jiang, J., Sun, N., & Shu, L. (2015). Secure communication for underwater acoustic sensor networks. IEEE Communications Magazine,53(8), 54–60.

    Article  Google Scholar 

  7. Han, G., Liu, L., Jiang, J., Shu, L., & Rodrigues, J. J. (2016). A collaborative secure localization algorithm based on trust model in underwater wireless sensor networks. Sensors,16(2), 229.

    Article  Google Scholar 

  8. Rezvani, M., Ignjatovic, A., Bertino, E., & Jha, S. (2014). Secure data aggregation technique for wireless sensor networks in the presence of collusion attacks. IEEE Transactions on Dependable and Secure Computing, 12(1), 98–110. (2015).

  9. Karimi, H., Medhati, O., Zabolzadeh, H., Eftekhari, A., Rezaei, F., & Dehno, S. B. (2015). Implementing a reliable, fault tolerance and secure framework in the wireless sensor-actuator networks for events reporting. Procedia Computer Science,73, 384–394.

    Article  Google Scholar 

  10. Xu, M., Liu, G., & Guan, J. (2015). Towards a secure medium access control protocol for cluster-based underwater wireless sensor networks. International Journal of Distributed Sensor Networks,11(5), 325474.

    Article  Google Scholar 

  11. Geetha, V., & Chandrasekaran, K. A. (2014). Distributed trust based secure communication framework for wireless sensor network. Wireless Sensor Network,6(9), 173.

    Article  Google Scholar 

  12. Kaur, J., Gill, S. S., & Dhaliwal, B. S. (2016). Secure trust based key management routing framework for wireless sensor networks. Journal of Engineering,2016, 1–9.

    Article  Google Scholar 

  13. Ahmed, M., Salleh, M., & Channa, M. I. (2018). CBE2R: Clustered-based energy efficient routing protocol for underwater wireless sensor network. International Journal of Electronics,105(11), 1916–1930.

    Article  Google Scholar 

  14. Goyal, N., Dave, M., & Verma, A. K. (2016). Energy efficient architecture for intra and inter cluster communication for underwater wireless sensor networks. Wireless Personal Communications,89(2), 687–707.

    Article  Google Scholar 

  15. Kumar, R. (2014). A survey on data aggregation and clustering schemes in underwater sensor networks. International Journal of Grid and Distributed Computing,7(6), 29–52.

    Article  Google Scholar 

  16. Xu, M., Liu, G., Zhu, D., & Wu, H. (2014). A cluster-based secure synchronization protocol for underwater wireless sensor networks. International Journal of Distributed Sensor Networks,10(4), 398610.

    Article  Google Scholar 

  17. Verma, S. (2015). A cluster based key management scheme for underwater wireless sensor networks. International Journal of Computer Network and Information Security,7(9), 54.

    Article  Google Scholar 

  18. Yuan, C., Chen, W., Zhu, Y., Li, D., & Tan, J. (2015). A low computational complexity authentication scheme in underwater wireless sensor network. In 11th IEEE international conference on mobile ad hoc and sensor networks (MSN) (pp. 116–123).

  19. Yun, C. W., Lee, J.H., Yi, O., & Park, S. H. (2016). Ticket-based authentication protocol for underwater wireless sensor network. In 8th IEEE international conference on ubiquitous and future networks (ICUFN) (pp. 215–217).

  20. Yavuz, A. A., & Ning, P. (2012). Self-sustaining, efficient and forward-secure cryptographic constructions for unattended wireless sensor networks. Ad Hoc Networks,10(7), 1204–1220.

    Article  Google Scholar 

  21. Ren, Y., Oleshchuk, V. A., & Li, F. Y. (2013). Optimized secure and reliable distributed data storage scheme and performance evaluation in unattended WSNs. Computer Communications,36(9), 1067–1077.

    Article  Google Scholar 

  22. Du, X., Peng, C., & Li, K. (2017). A secure routing scheme for underwater acoustic networks. International Journal of Distributed Sensor Networks,13(6), 1550147717713643.

    Article  Google Scholar 

  23. Dargahi, T., Javadi, H. H., & Shafiei, H. (2017). Securing underwater sensor networks against routing attacks. Wireless Personal Communications,96(2), 2585–2602.

    Article  Google Scholar 

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

    Article  Google Scholar 

  25. Goyal, N., Dave, M., & Verma, A. K. (2018). A novel fault detection and recovery technique for cluster-based underwater wireless sensor networks. International Journal of Communication Systems,31(4), e3485.

    Article  Google Scholar 

  26. Lee, S., Jeong, Y., Moon, E., & Kim, D. (2017). An efficient MOP decision method using hop interval for RPL-based underwater sensor networks. Wireless Personal Communications,93(4), 1027–1041.

    Article  Google Scholar 

  27. Goyal, N., Dave, M., & Verma, A. K. (2017). Improved data aggregation for cluster based underwater wireless sensor networks. Proceedings of the National Academy of Sciences, India, Section A: Physical Sciences,87(2), 235–245.

    Article  Google Scholar 

  28. Hamid, Z., & Hussain, F. B. (2014). QoS in wireless multimedia sensor networks: a layered and cross-layered approach. Wireless Personal Communications,75(1), 729–757.

    Article  Google Scholar 

  29. Kanthimathi, N. (2017). Balanced and multi-objective optimized opportunistic routing for underwater sensor networks. Wireless Personal Communications,94(4), 2417–2440.

    Article  Google Scholar 

  30. Zhao, X., Pompili, D., & Alves, J. (2017). Underwater acoustic carrier aggregation: Achievable rate and energy-efficiency evaluation. IEEE Journal of Oceanic Engineering,42(4), 1035–1048.

    Article  Google Scholar 

  31. Goyal, N., Dave, M., & Verma, A. K. (2019). Data aggregation in underwater wireless sensor network: Recent approaches and issues. Journal of King Saud University-Computer and Information Sciences,31(3), 275–286.

    Article  Google Scholar 

  32. Mohamed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2018). Survey on wireless sensor network applications and energy efficient routing protocols. Wireless Personal Communications,101(2), 1019–1055.

    Article  Google Scholar 

  33. Gomathi, R. M., & Manickam, J. M. L. (2018). Energy efficient shortest path routing protocol for underwater acoustic wireless sensor network. Wireless Personal Communications,98(1), 843–856.

    Article  Google Scholar 

  34. Ahmad, B., Jian, W., Enam, R. N., & Abbas, A. (2019). Classification of DoS attacks in smart underwater wireless sensor network. Wireless Personal Communications. https://doi.org/10.1007/s11277-019-06765-5.

    Article  Google Scholar 

  35. Mazinani, S. M., Yousefi, H., & Mirzaie, M. (2018). A vector-based routing protocol in underwater wireless sensor networks. Wireless Personal Communications,100(4), 1569–1583.

    Article  Google Scholar 

  36. Kim, S., & Yoo, Y. (2019). Practical multiple user system using heterogeneous frequency modulation for high data rate in underwater sensor network. Wireless Personal Communications,108, 1–24.

    Article  Google Scholar 

  37. Goyal, N., Sandhu, J. K., & Verma, L. (2019). Machine learning based data agglomeration in underwater wireless sensor networks. International Journal of Management, Technology and Engineering,9(6), 240–245.

    Google Scholar 

  38. Gomathi, R. M., & Manickam, J. M. L. (2019). Energy efficient static node selection in underwater acoustic wireless sensor network. Wireless Personal Communications,107, 1–19.

    Article  Google Scholar 

  39. Krishnaswamy, V., & Manvi, S. S. (2019). Fuzzy and PSO based clustering scheme in underwater acoustic sensor networks using energy and distance parameters. Wireless Personal Communications,108, 1–18.

    Article  Google Scholar 

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Authors and Affiliations

  1. Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India

    Nitin Goyal

  2. Department of Computer Engineering, National Institute of Technology, Kurukshetra, India

    Mayank Dave

  3. Department of Computer Science and Engineering, Thapar Institute of Engineering & Technology, Patiala, India

    Anil Kumar Verma

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  1. Nitin Goyal
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  2. Mayank Dave
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  3. Anil Kumar Verma
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Correspondence to Nitin Goyal.

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Goyal, N., Dave, M. & Verma, A.K. SAPDA: Secure Authentication with Protected Data Aggregation Scheme for Improving QoS in Scalable and Survivable UWSNs. Wireless Pers Commun 113, 1–15 (2020). https://doi.org/10.1007/s11277-020-07175-8

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  • DOI: https://doi.org/10.1007/s11277-020-07175-8

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