We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

Skip to main content
Log in

Block chain based trusted distributed routing scheme using optimized dropout ensemble extreme learning neural network in MANET

  • Published:
Peer-to-Peer Networking and Applications Aims and scope Submit manuscript

Abstract

Mobile ad hoc network (MANET) is a set of mobile nodes that communicate via wireless networks while moving from one place to another. Numerous studies have been done on increasing reliable between routing nodes, trust management, the use of cryptographic systems, and centralized routing decisions and so on. However, the majority of routing methods are challenging to execute in real-world scenarios, because it is challenging to determine the malicious behaviors of routing nodes. There is still no reliable method to prevent malicious node attacks. Due to these networks' dynamic and decentralized character, packet routing in MANET is difficult. To overcome this problem, this manuscript proposes a Dropout Ensemble Extreme Learning Neural Network (DrpEnXLNN) optimized with Metaheuristic Anopheles Search routing algorithm(MASA) based Token fostered Block chain Technology for trusted distributed optimal routing in Mobile adhoc networks. The aim of this work is to provide the most efficient method for data transmission and generates tokens for packet stream admittance with a secret key that goes to each routing mobile node. Subsequently, the trusted routing information is distributed by proposed block chain(BC) based mobile ad hoc network utilizing DrpEnXLNN optimized with MASA. The proposed technique is simulated in NS-2(Network Simulator) tool. The performance metrics, such as average delay, average latency, average energy consume, throughput of block chain token transactions are evaluated. Finally, the proposed TDRP-MASA-DrpEnXLNN-BCMANET method attains 22% and 14% less delay during 25% spiteful routing environment, 15% and 8% less delay during 50% spiteful routing environment when analyzed to the existing models.

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
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

Nil.

References

  1. Usman M, Jan MA, He X, Nanda P (2020) QASEC: A secured data communication scheme for mobile Ad-hoc networks. Futur Gener Comput Syst 109:604–610

    Article  Google Scholar 

  2. Tilwari V, Maheswar R, Jayarajan P, Sundararajan TVP, Hindia MHD, Dimyati K, Amiri IS (2020) MCLMR: A multicriteria based multipath routing in the mobile ad hoc networks. Wireless Pers Commun 112(4):2461–2483

    Article  Google Scholar 

  3. Krishnan RS, Julie EG, Robinson YH, Kumar R, Son LH, Tuan TA, Long HV (2020) Modified zone based intrusion detection system for security enhancement in mobile ad hoc networks. Wireless Netw 26(2):1275–1289

    Article  Google Scholar 

  4. Bhardwaj A, El-Ocla H (2020) Multipath routing protocol using genetic algorithm in mobile ad hoc networks. IEEE Access 8:177534–177548

    Article  Google Scholar 

  5. Roldán J, Boubeta-Puig J, Martínez JL, Ortiz G (2020) Integrating complex event processing and machine learning: An intelligent architecture for detecting IoT security attacks. Expert Syst Appl 149

    Article  Google Scholar 

  6. Gurung S, Chauhan S (2020) A survey of black-hole attack mitigation techniques in MANET: merits, drawbacks, and suitability. Wireless Netw 26(3):1981–2011

    Article  Google Scholar 

  7. El-Semary AM, Diab H (2019) BP-AODV: Blackhole protected AODV routing protocol for MANETs based on chaotic map. IEEE Access 7:95197–95211

    Article  Google Scholar 

  8. Panda N, Pattanayak BK (2018) Defense against co-operative black-hole attack and gray-hole attack in MANET.Int J Eng Technol 7(3.4):84–89

  9. Sivanesh S, Dhulipala VR (2021) Accurate and cognitive intrusion detection system (ACIDS): a novel black hole detection mechanism in mobile ad hoc networks. Mob Netw Appl 26(4):1696–1704

    Article  Google Scholar 

  10. Shajin FH, Rajesh P, Nagoji Rao VK (2022) Efficient Framework for Brain Tumour Classification using Hierarchical Deep Learning Neural Network Classifier.Comput Methods Biomech Biomed Eng Imaging Vis1–8

  11. Rajesh P, Shajin FH, Kumaran GK (2022) An Efficient IWOLRS Control Technique of Brushless DC Motor for Torque Ripple Minimization. Appl Sci Eng Prog 15(3):5514–5514

    Google Scholar 

  12. Shajin FH, Rajesh P (2020) Trusted secure geographic routing protocol: outsider attack detection in mobile ad hoc networks by adopting trusted secure geographic routing protocol.Int J Pervasive Comput Commun

  13. Rajesh P, Shajin F (2020) A multi-objective hybrid algorithm for planning electrical distribution system. Eur J Electr Eng 22(4–5):224–509

    Article  Google Scholar 

  14. Thota MK, Shajin FH, Rajesh P (2020) Survey on software defect prediction techniques. Int J Appl Sci 17(4):331–344

    Google Scholar 

  15. Montecchi M, Plangger K, Etter M (2019) It’s real, trust me! Establishing supply chain provenance using blockchain. Bus Horiz 62(3):283–293

    Article  Google Scholar 

  16. Gupta R, Tanwar S, Kumar N, Tyagi S (2020) Blockchain-based security attack resilience schemes for autonomous vehicles in industry 4.0: A systematic review.Comput Electr Eng86:106717

  17. Liu Y, Yu FR, Li X, Ji H, Leung VC (2020) Blockchain and machine learning for communications and networking systems. IEEE Commun Surv Tutor 22(2):1392–1431

    Article  Google Scholar 

  18. Makhdoom I, Zhou I, Abolhasan M, Lipman J, Ni W (2020) PrivySharing: A blockchain-based framework for privacy-preserving and secure data sharing in smart cities. Comput Secur 88

    Article  Google Scholar 

  19. Rahman MS, Khalil I, Moustafa N, Kalapaaking AP, Bouras A (2021) A blockchain-enabled privacy-preserving verifiable query framework for securing cloud-assisted industrial internet of things systems. IEEE Trans Industr Inf 18(7):5007–5017

    Article  Google Scholar 

  20. Ajao LA, Umar BU, Olajide DO, Misra S (2022) Application of crypto-blockchain technology for securing electronic voting systems. In Blockchain Applications in the Smart Era (85-105). Cham: Springer International Publishing

  21. Ren Y, Leng Y, Qi J, Sharma PK, Wang J, Almakhadmeh Z, Tolba A (2021) Multiple cloud storage mechanism based on blockchain in smart homes. Futur Gener Comput Syst 115:304–313

    Article  Google Scholar 

  22. Karale S, Ranaware V (2019) Applications of blockchain technology in smart city development: a research. Int J Innov Technol 8(11):556–559

    Google Scholar 

  23. Thebiga M, SujiPramila R (2020) A new mathematical and correlation coefficient based approach to recognize and to obstruct the black hole attacks in MANETs using DSR routing. Wireless Pers Commun 114(2):975–993

    Article  Google Scholar 

  24. Balaji S, Julie EG, Robinson YH, Kumar R, Thong PH (2019) Design of a security-aware routing scheme in mobile ad-hoc network using repeated game model. Comput Stand Interfaces 66:103358

    Article  Google Scholar 

  25. Kanagasundaram H, Kathirvel A (2019) EIMO-ESOLSR: energy efficient and security-based model for OLSR routing protocol in mobile ad-hoc network. IET Commun 13(5):553–559

    Article  Google Scholar 

  26. Wang X, Zhang P, Du Y, Qi M (2020) Trust routing protocol based on cloud-based fuzzy petri net and trust entropy for mobile ad hoc network. IEEE Access 8:47675–47693

    Article  Google Scholar 

  27. Wang T, Guo J, Ai S, Cao J (2021) RBT: A distributed reputation system for blockchain-based peer-to-peer energy trading with fairness consideration. Appl Energy 295

    Article  Google Scholar 

  28. Zhai J, Zang L, Zhou Z (2018) Ensemble dropout extreme learning machine via fuzzy integral for data classification. Neurocomputing 275:1043–1052

    Article  Google Scholar 

  29. Jiao Z, Zhang B, Zhang L, Liu M, Gong W, Li C (2020) A blockchain-based computing architecture for mobile Ad Hoc cloud. IEEE Netw 34(4):140–149

    Article  Google Scholar 

  30. Lwin MT, Yim J, Ko YB (2020) Blockchain-based lightweight trust management in mobile ad-hoc networks. Sensors 20(3):698

    Article  Google Scholar 

  31. Abdel-Sattar AS, Azer MA (2022) Using Blockchain Technology in MANETs Security. In2022 2nd International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC) 489-494. IEEE

  32. Manjula T, Anand B (2021) A secured multiplicative Diffie Hellman key exchange routing approach for mobile ad hoc network. J Ambient Intell Humaniz Comput 12(3):3621–3631

    Article  Google Scholar 

  33. Machado C, Westphall CM (2021) Blockchain incentivized data forwarding in MANETs: Strategies and challenges. Ad Hoc Netw 110

    Article  Google Scholar 

  34. Boddu N, Boba V, Vatambeti R (2022) A novel georouting potency based optimum spider monkey approach for avoiding congestion in energy efficient mobile ad-hoc network. 127(2):1157-1186

  35. Maruthupandi J, Prasanna S, Jayalakshmi P, Mareeswari V, Sanjeevi P (2021) Route manipulation aware software-defined networks for effective routing in SDN controlled MANET by disney routing protocol. Microprocess Microsyst 80

    Article  Google Scholar 

  36. Raja L, Periasamy PS (2022) A Trusted distributed routing scheme for wireless sensor networks using block chain and jelly fish search optimizer based deep generative adversarial neural network (Deep-GANN) technique. Wireless Pers Commun 126(2):1101–1128

    Article  Google Scholar 

Download references

Acknowledgements

Not Applicable.

Funding

None.

Author information

Authors and Affiliations

Authors

Contributions

V. Krishnakumar - Conceptualization Methodology, Original draft preparation R. Asokan- Supervision.

Corresponding author

Correspondence to V. Krishnakumar.

Ethics declarations

Ethical approval and consent to participate

Nil.

Consent for publication

Nil.

Competing interests

Nil.

Human and animal ethics

Nil.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krishnakumar, V., Asokan, R. Block chain based trusted distributed routing scheme using optimized dropout ensemble extreme learning neural network in MANET. Peer-to-Peer Netw. Appl. 16, 2696–2713 (2023). https://doi.org/10.1007/s12083-023-01551-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12083-023-01551-4

Keywords

Navigation