Skip to main content

Advertisement

SpringerLink
Log in

Novel Fuzzy Based Crow Search Optimization Algorithm for Secure Node-to-Node Data Transmission in WSN

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Various sensor nodes are interconnected with each other in wireless sensor network (WSN). WSN communicates to every node within the network wirelessly to collect data regarding the surrounding environment and send the particular data to the destination/centralised location. The sensor nodes transmit the data and the source sensor node transmits data to destination sensor nodes through various intermediary sensor nodes. Thus, secure transmission is required in which WSN must be free from malicious nodes to achieve safe transfer. In this paper, our objective is to provide secure data transmission in an efficient manner from source to destination through a trust based path namely novel fuzzy based crow search optimization algorithm (F-CSO) and optimised link state routing protocol (OLSR) protocol. Through NS3 tool, nodes are deployed in the network area and novel F-CSO is performed with respect to three parameters such as distance, degree and transmission energy. The best nodes are considered for optimization process and it must satisfy the three conditions such as lower distance between each node for transmitting the data, higher degree and higher energy for transmission. A set of nodes that satisfies this condition are gathered by the fuzzy rule technique and then further optimised by crow search optimization technique leading to exact nodes through which trust based transmissions are performed. Further, routing can be achieved by the OLSR protocol. The performance of the proposed system is compared with existing studies with respect to the system for detecting the malicious nodes with and without utilizing proposed F-CSO in terms of execution time, throughput, and packet delivery ratio. The evaluation result has shown that malicious nodes is detected in an efficient manner through the use of F-CSO, showing better results with various parameters.

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Mahajan, S., & Dhiman, P. K. (2016). Clustering in wireless sensor networks: A review. International Journal of Advanced Research in Computer Science, 7(3), 198–201.

    Google Scholar 

  2. Mugheri, A. A., Siddiqui, M. A., & Khoso, M. (2018). Analysis on security methods of wireless sensor network (WSN). Sukkur IBA Journal of Computing and Mathematical Sciences, 2(1), 52–60.

    Article  Google Scholar 

  3. Mallick, C., & Satpathy, S. (2018). Challenges and design goals of wireless sensor networks: A state-of-the-art review. International Journal of Computer Applications, 179(28), 42–47.

    Article  Google Scholar 

  4. Elhoseny M., & Hassanien A. E. (2019). Secure data transmission in WSN: An overview. In Dynamic wireless sensor networks. Studies in systems, decision and control (vol. 165). Springer.

  5. Gaber, T., Abdelwahab, S., Elhoseny, M., & Hassanien, A. E. (2018). Trust-based secure clustering in WSN-based intelligent transportation systems. Computer Networks, 146, 151–158.

    Article  Google Scholar 

  6. Silva, H., Hahn Pereira, A., Solano, Y., de Oliveira, Bruno T., & Margi, Cıntia B. (2016). Warm: WSN application development and resource management. XXXIV Simpsio Brasileiro de Telecomunicaes e Processamento de Sinais. Santarm, Brazil: Sociedade Brasileira de Telecomunicaes.

  7. Cocîrlea, D., Dobre, C., Hîrţan, L.-A., & Purnichescu-Purtan, R. (2020). Blockchain in intelligent transportation systems. Electronics, 9(10), 1682.

    Article  Google Scholar 

  8. van der Heijden, R. W., Dietzel, S., Leinmüller, T., & Kargl, F. (2018). Survey on misbehavior detection in cooperative intelligent transportation systems. IEEE Communications Surveys and Tutorials, 21(1), 779–811.

    Article  Google Scholar 

  9. Liang, W., Huang, Y., Jianbo, X., & Xie, S. (2017). A distributed data secure transmission scheme in wireless sensor network. International Journal of Distributed Sensor Networks, 13(4), 1550147717705552.

    Article  Google Scholar 

  10. Qureshi, S. G., & Shandilya, S. K. (2019). Advances in cyber security paradigm: A review. In International conference on hybrid intelligent systems (pp. 268–276). Springer.

  11. Usman, M., Jan, M. A., He, X., & Chen, J. (2018). A mobile multimedia data collection scheme for secured wireless multimedia sensor networks. IEEE Transactions on Network Science and Engineering, 7(1), 274–284.

    Article  Google Scholar 

  12. Han, G., Jiang, J., Guizani, M., & Rodrigues, J. J. P. C. (2016). Green routing protocols for wireless multimedia sensor networks. IEEE Wireless Communications, 23(6), 140–146.

    Article  Google Scholar 

  13. Sumalatha, M. S., & Nandalal, V. (2020). An intelligent cross layer security based fuzzy trust calculation mechanism (CLS-FTCM) for securing wireless sensor network (WSN). Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-020-01834-1

  14. Radhappa, H., Pan, L., Zheng, J. X., & Wen, S. (2018). Practical overview of security issues in wireless sensor network applications. International Journal of Computers and Applications, 40(4), 202–213.

    Article  Google Scholar 

  15. Razaque, A., & Rizvi, S. S. (2017). Secure data aggregation using access control and authentication for wireless sensor networks. Computers and Security, 70, 532–545.

    Article  Google Scholar 

  16. Karthick, S. (2018). Tdp: A novel secure and energy aware routing protocol for wireless sensor networks. International Journal of Intelligent Engineering and Systems, 11(2), 76–84.

    Article  Google Scholar 

  17. Preeth, S. K. S. L., Dhanalakshmi, R., Kumar, R., et al. (2018). An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-018-1154-z

    Article  Google Scholar 

  18. Chandrakanth, H. G., Anand, D. G., John Peter, T., et al. (2017). Research challenges and characteristic features in wireless sensor networks. International Journal of Advanced Networking and Applications, 9(1), 3321.

    Google Scholar 

  19. Rodrigues, P., & John, J. (2020). Joint trust: An approach for trust-aware routing in WSN. Wireless Networks, 5, 1–16.

    Google Scholar 

  20. Tao Yang, X., Xiangyang, L. P., Tonghui, L., & Leina, P. (2018). A secure routing of wireless sensor networks based on trust evaluation model. Procedia Computer Science, 131, 1156–1163.

    Article  Google Scholar 

  21. Scholar, P. G. (2016). Trust value estimation for secure data forwarding in wireless sensor network. International Journal of Future Innovative Science and Engineering Research (IJFISER), 2(2), 186.

    Google Scholar 

  22. Xie, H., Yan, Z., Yao, Z., & Atiquzzaman, M. (2018). Data collection for security measurement in wireless sensor networks: A survey. IEEE Internet of Things Journal, 6(2), 2205–2224.

    Article  Google Scholar 

  23. John, J., & Rodrigues, P. (2019). Motco: Multi-objective Taylor crow optimization algorithm for cluster head selection in energy aware wireless sensor network. Mobile Networks and Applications, 24(5), 1509–1525.

    Article  Google Scholar 

  24. Li, B., Xiao, S., & Li, Y. (2019). Networking and communications for the next generation IoT. Mobile Networks and Applications, 24(5), 1411–1413.

    Article  Google Scholar 

  25. Singh, Hr, Tyagi, S., & Kumar, P. (2019). Crow search based scheduling algorithm for load balancing in cloud environment. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(9), 1058–1064.

    Article  Google Scholar 

  26. El-Saeed, M., El-Hameed, M., & AbdElGwaad, A. (2018). Crow search algorithm for allocation of multi-type distributed generation in unbalanced radial distribution system. Egyptian Journal for Engineering Sciences and Technology, 25, 7–23.

    Article  Google Scholar 

  27. Mahesh, N., & Vijayachitra, S. (2019). Decsa: hybrid dolphin echolocation and crow search optimization for cluster-based energy-aware routing in WSN. Neural Computing and Applications, 31(1), 47–62.

    Article  Google Scholar 

  28. Sahoo, B. M., Pandey, H. M., & Amgoth, T. (2020). Gapso-h: A hybrid approach towards optimizing the cluster based routing in wireless sensor network. Swarm and Evolutionary Computation, 60, 100772.

    Article  Google Scholar 

  29. Ouldzira, H., Mouhsen, A., Lagraini, H., Chhiba, M., Tabyaoui, A., & Amrane, S. (2019). Remote monitoring of an object using a wireless sensor network based on nodemcu esp8266. Indonesian Journal of Electrical Engineering and Computer Science, 16(3), 1154–1162.

    Article  Google Scholar 

  30. Gupta, D., Khanna, A., Lakshmanaprabu, S. K., Shankar, K., Furtado, V., & Rodrigues, J. J. P. C. (2019). Efficient artificial fish swarm based clustering approach on mobility aware energy-efficient for manet. Transactions on Emerging Telecommunications Technologies, 30(9), e3524.

    Article  Google Scholar 

  31. Meraihi, Y., Gabis, A. B., Ramdane-Cherif, A., & Acheli, D. (2020). A comprehensive survey of crow search algorithm and its applications. Artificial Intelligence Review. https://doi.org/10.1007/s10462-020-09911-9

    Article  Google Scholar 

  32. Vani, Y. K., & Ranjana, P. (2020). Detection of distributed denial of service attack using DLMN algorithm in hadoop. Journal of Critical Review, 7(11), 1011–1017.

    Google Scholar 

  33. Manimurugan, S., Majdi, A., Mohmmed, M., Narmatha, C., & Varatharajan, R. (2020). Intrusion detection in networks using crow search optimization algorithm with adaptive neuro-fuzzy inference system. Microprocessors and Microsystems, 79, 103261.

    Article  Google Scholar 

  34. Thangaramya, K., Kulothungan, K., Indira Gandhi, S., Selvi, M., Santhosh Kumar, S. V. N., & Arputharaj, K. (2020). Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN. Soft Computing, 24(21), 16483–16497.

    Article  Google Scholar 

  35. Umar, I. A., Hanapi, Z. M., Sali, A., & Zulkarnain, Z. A. (2017). Trufix: A configurable trust-based cross-layer protocol for wireless sensor networks. IEEE Access, 5, 2550–2562.

    Article  Google Scholar 

  36. Mehmood, G., Khan, M. Z., Waheed, A., Zareei, M., & Mohamed, E. M. (2020). A trust-based energy-efficient and reliable communication scheme (trust-based ERCS) for remote patient monitoring in wireless body area networks. IEEE Access, 8, 131397–131413.

    Article  Google Scholar 

  37. Arif, A., Zubair, M., Ali, M., Khan, M. U., & Mehmood, M. Q. (2019). A compact, low-profile fractal antenna for wearable on-body WBAN applications. IEEE Antennas and Wireless Propagation Letters, 18(5), 981–985.

    Article  Google Scholar 

  38. Dahman Alshehri, M., & Hussain, F. K. (2019). A fuzzy security protocol for trust management in the internet of things (fuzzy-IoT). Computing, 101(7), 791–818.

    Article  MathSciNet  Google Scholar 

  39. Beghriche, A., & Bilami, A. (2018). A fuzzy trust-based routing model for mitigating the misbehaving nodes in mobile ad hoc networks. International Journal of Intelligent Computing and Cybernetics, 11(2), 309–340.

    Article  Google Scholar 

  40. Gomathi, K., Parvathavarthini, B., & Saravanakumar, C. (2017). An efficient secure group communication in manet using fuzzy trust based clustering and hierarchical distributed group key management. Wireless Personal Communications, 94(4), 2149–2162.

    Article  Google Scholar 

  41. Mhetre, N. A., Deshpande, A. V., & Mahalle, P. N. (2016). Trust management model based on fuzzy approach for ubiquitous computing. International Journal of Ambient Computing and Intelligence (IJACI), 7(2), 33–46.

    Article  Google Scholar 

  42. Rajeswari, A. R., Kulothungan, K., Ganapathy, S., & Kannan, A. (2019). A trusted fuzzy based stable and secure routing algorithm for effective communication in mobile adhoc networks. Peer-to-Peer Networking and Applications, 12(5), 1076–1096.

    Article  Google Scholar 

  43. Ram Prabha, V., & Latha, P. (2017). Fuzzy trust protocol for malicious node detection in wireless sensor networks. Wireless Personal Communications, 94(4), 2549–2559.

    Article  MATH  Google Scholar 

  44. Singh, Rupinder, Singh, Jatinder, & Singh, Ravinder. (2017). Fuzzy based advanced hybrid intrusion detection system to detect malicious nodes in wireless sensor networks. Wireless Communications and Mobile Computing. https://doi.org/10.1155/2017/3548607

    Article  Google Scholar 

  45. Devi, V. S., & Hegde, N. P. (2018). Multipath security aware routing protocol for manet based on trust enhanced cluster mechanism for lossless multimedia data transfer. Wireless Personal Communications, 100(3), 923–940.

    Article  Google Scholar 

  46. Saidi, A., Benahmed, K., & Seddiki, N. (2020). Secure cluster head election algorithm and misbehavior detection approach based on trust management technique for clustered wireless sensor networks. Ad Hoc Networks, 106, 102215.

    Article  Google Scholar 

  47. Kumar, S. R., & Gayathri, N. (2016). Trust based data transmission mechanism in manet using SOLSR. In Annual Convention of the Computer Society of India (pp. 169–180). Springer.

  48. Mukhedkar, M. M., & Kolekar, U. (2019). Trust-based secure routing in mobile ad hoc network using hybrid optimization algorithm. The Computer Journal, 62(10), 1528–1545.

    Article  MathSciNet  Google Scholar 

  49. Kanagasundaram, H., & Ayyaswamy, K. (2019). Multi objective ALO based energy efficient and secure routing OLSR protocol in manet. International Journal of Intelligent Engineering and Systems, 12(1), 74–83.

    Article  Google Scholar 

  50. Zhang, D., Cui, Y., & Zhang, T. (2019). New quantum-genetic based OLSR protocol (GG-OLSR) for mobile ad hoc network. Applied Soft Computing, 80, 285–296.

    Article  Google Scholar 

  51. Singh, A., Singh, G., & Singh, M. (2018). Comparative study of olsr, dsdv, aodv, dsr and zrp routing protocols under blackhole attack in mobile ad hoc network. In Intelligent Communication, control and devices (pp. 443–453). Springer.

  52. Saddiki, K., Boukli-Hacene, S., Lorenz, P., & Gilg, M. (2017). Black hole attack detection and ignoring in OLSR protocol. International Journal of Trust Management in Computing and Communications, 4(1), 75–93.

    Article  Google Scholar 

  53. Najafpour, B., Mahdavi, B., Soleimani, P., & Rahmani, R. (2016). Optimizing security issue of OLSR routing protocol based on trust method in wireless sensor networks. International Journal of Research in Computer Applications and Robotics, 4(3), 27–37.

    Google Scholar 

  54. Deebak, B. D., & Al-Turjman, F. (2020). A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks. Ad Hoc Networks, 97, 102022.

    Article  Google Scholar 

  55. Brar, G. S., Rani, S., Chopra, V., Malhotra, R., Song, H., & Ahmed, S. H. (2016). Energy efficient direction-based PDORP routing protocol for WSN. IEEE Access, 4, 3182–3194.

    Article  Google Scholar 

  56. Bagyalakshmi, P., & Anitha, R. (2015). Secure data transmission in wireless sensor network using MP-OLSR. International Journal of Communication and Networking System, 4, 97–101.

    Article  Google Scholar 

  57. Heidari, A. A., Abbaspour, R. A., & Jordehi, A. R. (2017). An efficient chaotic water cycle algorithm for optimization tasks. Neural Computing and Applications, 28(1), 57–85.

    Article  Google Scholar 

  58. Heidari, A. A., Abbaspour, R. A., & Jordehi, A. R. (2017). Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems. Applied Soft Computing, 57, 657–671.

    Article  Google Scholar 

  59. Aashmi, R. S., Santhana, J., & Jeeva, S. (2017). Ranked key search and efficient retrieval of grand data on cloud computing. Indian Journal of Research Foundation, 6, 24–29.

    Google Scholar 

  60. Mirjalili, S., Mirjalili, S. M., & Yang, X.-S. (2014). Binary bat algorithm. Neural Computing and Applications, 25(3), 663–681.

    Article  Google Scholar 

  61. Sameswari, V., & Ramaraj, E. (2014). Shortest route discovery using hybrid (AODV and OLSR) routing protocols in manet. In UGC sponsored national conference on data science and engineering-proceedings (pp. 273–279). Elsevier.

Download references

Author information

Authors and Affiliations

  1. VIT Bhopal University, Bhopal, India

    Shahana Gajala Qureshi & Shishir Kumar Shandilya

Authors
  1. Shahana Gajala Qureshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shishir Kumar Shandilya
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shishir Kumar Shandilya.

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

Qureshi, S.G., Shandilya, S.K. Novel Fuzzy Based Crow Search Optimization Algorithm for Secure Node-to-Node Data Transmission in WSN. Wireless Pers Commun 127, 577–597 (2022). https://doi.org/10.1007/s11277-021-08352-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08352-z

Keywords

Search

Navigation