Enhanced cryptography algorithm and improved butterfly algorithm for secured data transmission in wireless sensor network

Authors

  • A. Prakash Department of Computer Applications (PG). Hindusthan College of Arts & Science Coimbatore. Chennai, India. Author
  • M. Prakash Department of Computer Applications (PG). Hindusthan College of Arts & Science Coimbatore. Chennai, India. Author

DOI:

https://doi.org/10.56294/sctconf2023593

Keywords:

Wireless Sensor Networks (WSNs), Cluster Head (CH), Based Improved Butterfly Optimization (IBO), Algorithm and Double Key Based Advanced Encryption Standard (DAES), Algorithm

Abstract

Due of their many uses, WSNs (Wireless Sensor Networks) have drawn the greatest interest, but, existing methods do not support reliable data transfer. They face issues in energy consumptions and routing on shortest paths over WSNs. Also, they are incapable to stopping compromised nodes with legitimate identities from launching attacks. This study handled this issue with suggested schema based on CHs (Cluster Heads) and using IBO (Improved Butterfly Optimization) and DAES (Double key based Advanced Encryption Standard) algorithms. The main phases of this work contain system model, security model, CH node selection and shortest path routing with secured data transmission. Initially, system model is constructed via number of sensor nodes on the given setup. Then, CH nodes are selected using IBO algorithm based on best fitness values. These selections of CHs consider minimum delays and energy consumptions with maximum throughputs for establishing security assurances and energy conservations at sensor nodes along with secure protocol. The security levels for quick data transfers over multi-path routes in WSNs are improved using DAES. Attack nodes are eliminated for successful transfers. The intermediate layer CHs create routing backbones to gather, combine, and convey data from member nodes. The simulation results demonstrate that the proposed IBO-DAES framework outperforms existing approaches in terms of throughputs, network longevity, data transfer rates, and energy consumptions.

References

1. Yang, Liu, et al. "An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks." Telecommunication Systems 68 (2018): 11-26.

2. Yang, Guisong, et al. "Global and local reliability-based routing protocol for wireless sensor networks." IEEE Internet of Things Journal 6.2 (2018): 3620-3632.

3. Thakkar, Ankit, and Ketan Kotecha. "Cluster head election for energy and delay constraint applications of wireless sensor network." IEEE sensors Journal 14.8 (2014): 2658-2664.

4. Saleh, Nayif, Abdallah Kassem, and Ali M. Haidar. "Energy-efficient architecture for wireless sensor networks in healthcare applications." IEEE Access 6 (2018): 6478-6486

5. Fu, Xiuwen, et al. "Environment-fusion multipath routing protocol for wireless sensor networks." Information Fusion 53 (2020): 4-19.

6. Raghavendra, Y. M., and U. B. Mahadevaswamy. "Energy efficient routing in wireless sensor network based on composite fuzzy methods." Wireless Personal Communications 114.3 (2020): 2569-2590

7. Ayadi, Hayfa, et al. "Network lifetime management in wireless sensor networks." IEEE Sensors Journal 18.15 (2018): 6438-6445

8. Elshrkawey, Mohamed, Samiha M. Elsherif, and M. ElsayedWahed. "An enhancement approach for reducing the energy consumption in wireless sensor networks." Journal of King Saud University-Computer and Information Sciences 30.2 (2018): 259-267

9. Tabibi, Shamineh, and Ali Ghaffari. "Energy-efficient routing mechanism for mobile sink in wireless sensor networks using particle swarm optimization algorithm." Wireless Personal Communications 104.1 (2019): 199-216.

10. Ñope EMG, Claudio BAM, Ruiz JAZ. The Service Quality of a Feed Industry Company. Southern Perspective / Perspectiva Austral 2023;1:9–9. https://doi.org/10.56294/pa20239.

11. Jeronimo CJC, Basilio AYP, Claudio BAM, Ruiz JAZ. Human talent management and the work performance of employees in a textile company in Comas. Southern Perspective / Perspectiva Austral 2023;1:5–5. https://doi.org/10.56294/pa20235.

12. Mahajan, Shilpa, Jyoteesh Malhotra, and Sandeep Sharma. "An energy balanced QoS based cluster head selection strategy for WSN." Egyptian Informatics Journal 15.3 (2014): 189-199

13. Saidi, Ahmed, Khelifa Benahmed, and Nouredine Seddiki. "Secure cluster head election algorithm and misbehavior detection approach based on trust management technique for clustered wireless sensor networks." Ad Hoc Networks 106 (2020): 102215

14. Han, Guangjie, et al. "Intrusion detection algorithm based on neighbor information against sinkhole attack in wireless sensor networks." The Computer Journal 58.6 (2015): 1280-1292

15. Dionicio RJA, Serna YPO, Claudio BAM, Ruiz JAZ. Sales processes of the consultants of a company in the bakery industry. Southern Perspective / Perspectiva Austral 2023;1:2–2. https://doi.org/10.56294/pa20232.

16. Velásquez AA, Gómez JAY, Claudio BAM, Ruiz JAZ. Soft skills and the labor market insertion of students in the last cycles of administration at a university in northern Lima. Southern Perspective / Perspectiva Austral 2024;2:21–21. https://doi.org/10.56294/pa202421.

17. Abikoye, Oluwakemi Christiana, et al. "Modified advanced encryption standard algorithm for information security." Symmetry 11.12 (2019): 1484

18. Chan, Wai Hong Ronald, et al. "Adaptive duty cycling in sensor networks with energy harvesting using continuous-time Markov chain and fluid models." IEEE Journal on Selected Areas in Communications 33.12 (2015): 2687-2700

19. Arora, S. and Singh, S., 2019. Butterfly optimization algorithm: a novel approach for global optimization. Soft Computing, 23(3), pp.715-734.

20. Tubishat, M., Alswaitti, M., Mirjalili, S., Al-Garadi, M.A. and Rana, T.A., 2020. Dynamic butterfly optimization algorithm for feature selection. IEEE Access, 8, pp.194303-194314

21. Panda, Madhumita. "Data security in wireless sensor networks via AES algorithm." 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO). IEEE, 2015

22. Zhang, De-gan, et al. "Extended AODV routing method based on distributed minimum transmission (DMT) for WSN." AEU-International Journal of Electronics and Communications 69.1 (2015): 371-381

23. Yang, Liu, et al. "An evolutionary game-based secure clustering protocol with fuzzy trust evaluation and outlier detection for wireless sensor networks." IEEE Sensors Journal 21.12 (2021): 13935-13947.

24. Augustine, Susan, and John Patrick Ananth. "Taylor kernel fuzzy C-means clustering algorithm for trust and energy-aware cluster head selection in wireless sensor networks." Wireless Networks 26 (2020): 5113-5132.

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Published

2023-10-24

How to Cite

1.
Prakash A, Prakash M. Enhanced cryptography algorithm and improved butterfly algorithm for secured data transmission in wireless sensor network. Salud, Ciencia y Tecnología - Serie de Conferencias [Internet]. 2023 Oct. 24 [cited 2025 Apr. 19];2:593. Available from: https://conferencias.ageditor.ar/index.php/sctconf/article/view/494