Skip to main content
SpringerLink
Log in

An Efficient Wormhole Detection and Optimal Path Selection for Secure Data Transmission in WSN Environment

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Recently, the Wormhole Attack (WA) affects the Wireless Sensor Networks (WSN). So far, there are ‘2’ solutions to trounce WA, that is, utilizing specialized hardware or capturing a specific pattern extra overhead over the network. Some prevailing solutions for detectingWAneed special hardware or firmly synchronized clocks or longer processing time in addition to that some solutions can’t even locate the WormHole (WH) and also have low security.This paper proposed an efficient WH detection as well as Optimal Path (OP) selection for safe Data Transmission (DT) in WSN. The proposed workencompasses a '2' phase: i) training, and ii) testing. Here, the WSN values are considered and chosen secure node utilizing the Fit Factor (FF). After selecting the secure nodes, the routes are discovered aimed at the optimal assortment of the optimal routes. Next, the gathered data is tested with a trained system in which feature reduction and classification are performed. Lastly, the MCSC securely transfers the non-attack data. The proposed method’s outcomes are examined and weighed against the other prevailing techniques and the outcomesexhibited the proposed method’s efficiency for attack detection along withdata security.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

References

  1. Sharma, M., Tandon, A., Narayan, S., & Bhushan, B. (2017). Classification and analysis of security attacks in WSNs and IEEE 802.15. 4 standards: A survey. In 2017 3rd International conference on advances in computing, communication & automation (ICACCA) (Fall) (pp. 1–5). IEEE

  2. Fotohi, R., & Bari, S. F. (2020). A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms. The Journal of Supercomputing, 1–27. https://doi.org/10.1007/s11227-019-03131-x

  3. Jhanjhi, N. Z, Brohi, S. N., & Malik, N. A. (2019). Proposing a rank and wormhole attack detection framework using machine learning. In 13th international conference on mathematics, actuarial science, computer science and statistics (MACS) (pp. 1–9). IEEE

  4. Singh, M. M., Dutta, N., Singh, T. R, & Nandi, U. (2020). A technique to detect wormhole attack in wireless sensor network using artificial neural network. In Evolutionary computing and mobile sustainable networks (pp. 297–307). Springer. https://doi.org/10.1007/978-981-15-5258-8_29

  5. Kandris, D., Nakas, C., Vomvas, D., & Koulouras, G. (2020). Applications of wireless sensor networks: An up-to-date survey. Applied System Innovation, 3(1), 14.

    Article  Google Scholar 

  6. Bhushan, B., & Sahoo, G. (2020). ISFC-BLS (intelligent and secured fuzzy clustering algorithm using balanced load sub-cluster formation) in WSN environment. Wireless Personal Communications, 111(3), 1667–1694. https://doi.org/10.1007/s11277-019-06948-0

    Article  Google Scholar 

  7. Carlos-Mancilla, M., López-Mellado, E., & Siller, M. (2016). Wireless sensor networks formation: Approaches and techniques. Journal of Sensors. https://doi.org/10.1155/2016/2081902

    Article  Google Scholar 

  8. Amish, P., & Vaghela, V. B. (2016). Detection and prevention of wormhole attack in wireless sensor network using AOMDV protocol. Procedia Computer Science, 79, 700–707. https://doi.org/10.1016/j.procs.2016.03.092

    Article  Google Scholar 

  9. Opeyemi Osanaiye, A., Alfa, A. S., & Hancke, G. P. (2018). Denial of service defence for resource availability in wireless sensor networks. IEEE Access, 6, 6975–7004. https://doi.org/10.1109/ACCESS.2018.2793841

    Article  Google Scholar 

  10. Farjamnia, G., Gasimov, Y., & Kazimov, C. (2019). Review of the techniques against the wormhole attacks on wireless sensor networks. Wireless Personal Communications, 105(4), 1561–1584. https://doi.org/10.1007/s11277-019-06160-0

    Article  Google Scholar 

  11. Jilani, S. A., Koner, C., & Nandi, S. (2020). Security in wireless sensor networks: Attacks and evasion. In National conference on emerging trends on sustainable technology and engineering applications (NCETSTEA) (pp. 1–5). IEEE

  12. Foley, J., Moradpoor, N., & Ochen, H. (2020). Employing a machine learning approach to detect combined internet of things attacks against two objective functions using a novel dataset. Security and Communication Networks. https://doi.org/10.1155/2020/2804291

    Article  Google Scholar 

  13. Boni, K. R. C., Xu, L., Chen, Z., & Baddoo, T. D. (2020). A security concept based on scaler distribution of a novel intrusion detection device for wireless sensor networks in a smart environment. Sensors, 20(17), 4717.

    Article  Google Scholar 

  14. Pundir, S., Wazid, M., Singh, D. P., Das, A. K., Rodrigues, J. J. P. C., & Park, Y. (2020). Designing efficient sinkhole attack detection mechanism in edge-based IoT Deployment. Sensors, 20(5), 1300.

    Article  Google Scholar 

  15. Gómez, J. R., Montoya, H. F. V., & Henao, A. L. (2019). Implementación del ataque Wormhole en redes de sensores inalámbricos con dispositivos XBee S2C. Rev Colomb de Computación, 20(1), 41–58.

    Article  Google Scholar 

  16. Dwivedi, R. K., Sharma, P, & Kumar, R. (2018). Detection and prevention analysis of wormhole attack in wireless sensor network. In 2018 8th international conference on cloud computing, data science & engineering (confluence) (pp. 727–732). IEEE

  17. Harsányi, K., Kiss, A., & Szirányi, T. (2018). Wormhole detection in wireless sensor networks using spanning trees. In IEEE international conference on future IoT technologies (Future IoT) (pp. 1–6). IEEE

  18. Verma, M. K., & Dwivedi, R. K. (2020). A survey on wormhole attack detection and prevention techniques in wireless sensor networks. In International conference on electrical and electronics engineering (ICE3) (pp. 326–331). IEEE

  19. Solangi, S. A., & Bhatti, Z. (2020). Optimal route planning by genetic algorithm for wireless sensor networks. In International conference on information science and communication technology (ICISCT) (pp. 1–4). IEEE

  20. Qureshi, K. N., Bashir, M. U., Lloret, J., & Leon, A. (2020). Optimized cluster-based dynamic energy-aware routing protocol for wireless sensor networks in agriculture precision. Journal of Sensors. https://doi.org/10.1155/2020/9040395

    Article  Google Scholar 

  21. Mezni, A., Dumitrescu, E., Niel, E., & Ahmed, S. B. (2018). Multi criteria automatic generation of optimal routing for WSN. In 14th international wireless communications & mobile computing conference (IWCMC) (pp. 747–752). IEEE

  22. Tang, L., Lu, Z., & Fan, B. (2020). Energy efficient and reliable routing algorithm for wireless sensors networks. Applied Sciences, 10(5), 1885.

    Article  Google Scholar 

  23. Aghbari, Z. A., Khedr, A. M., Osamy, W., Arif, I., & Agrawal, D. P. (2019). Routing in wireless sensor networks using optimization techniques: A survey. Wireless Personal Communications, 1–28. https://doi.org/10.1007/s11277-019-06993-9

  24. Tamilarasi, N., & Santhi, S. G. (2020). Detection of wormhole attack and secure path selection in wireless sensor network. Wireless Personal Communications, 114(1), 329–345.

    Article  Google Scholar 

  25. Johnson, M. O., Siddiqui, A., & Karami, A. (2017). A wormhole attack detection and prevention technique in wireless sensor networks. International Journal of Computer Applications, 174(4), 1–8.

    Article  Google Scholar 

  26. Kumar, M., & Dutta, K. (2017). Detecting wormhole attack on data aggregation in hierarchical WSN. International Journal of Information Security and Privacy (IJISP), 11(1), 35–51.

    Article  Google Scholar 

  27. Singh, R., Singh, J., & Singh, R. (2016). WRHT: A hybrid technique for detection of wormhole attack in wireless sensor networks. Mobile Information Systems. https://doi.org/10.1155/2016/8354930

  28. Luo, X., Chen, Y., Li, M., Luo, Q., Xue, K., Liu, S., & Chen, L. (2019). CREDND: A novel secure neighbor discovery algorithm for wormhole attack. IEEE Access, 7, 18194–18205. https://doi.org/10.1109/ACCESS.2019.2894637

    Article  Google Scholar 

  29. Neelamadhab Padhy Gomathy, V., Samanta, D., Sivaram, M., Jain, V., & Amiri, I. S. (2020). Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks. Journal of Ambient Intelligence and Humanized Computing, 1–7. https://doi.org/10.1007/s12652-020-01797-3

Download references

Acknowledgements

We thank the anonymous referees for their useful suggestions.

Funding

None.

Author information

Authors and Affiliations

  1. Computer Science and Engineering, Birla Institute of Technology, Mesra, Ranchi, India

    Vanita Verma & Vijay Kumar Jha

Authors
  1. Vanita Verma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vijay Kumar Jha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vanita Verma.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

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

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

Verma, V., Jha, V.K. An Efficient Wormhole Detection and Optimal Path Selection for Secure Data Transmission in WSN Environment. Wireless Pers Commun 121, 2927–2945 (2021). https://doi.org/10.1007/s11277-021-08856-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08856-8

Keywords

Search

Navigation