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Elliptic Curve Cryptography Based Authentication Protocol Enabled with Optimized Neural Network Based DoS Mitigation

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A Correction to this article was published on 17 March 2022

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Abstract

In WSN based real-time applications, the authentication scheme is not yet defined properly under the consideration of user privacy. Even though lot of attempts have been made for introducing the lightweight anonymous authentication protocol in WSN based real-time applications, the risk due to denial-of-service (DoS) attacks is not yet rectified completely. The protocols are in need of compromising the un-link ability property to rebuild the synchronization among participants. To deal with the DoS detection and mitigation, in this paper, a new efficient and DoS-resistant user authentication scheme with the incorporation of ECC based authentication protocol is introduced. The implemented protocol involves four phases namely (i) User Registration phase (ii) Remedy phase (iii) Attack prediction phase, and (iv) Reloading phase. This proposed work mainly contemplates over the attack prediction phase, where the Neural Network (NN) model is deployed for the detection of DoS attack. As the main contribution, the training of NN is done by optimization concept in terms of selecting the optimal weight of NN. For the training purpose, a new improved algorithm named, Fitness Indexed Whale Optimization Algorithm (FI-WOA), which is the modification of the WOA algorithm. Finally, the performance of proposed work is compared over other state-of-the-art models and proves its superiority.

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Change history

  • 19 March 2022

    The original version of this article was revised: In the original version of this article the affiliation details for authors Sobini X. Pushpa and S. Kanaga Suba Raja were incorrectly assigned. The original article has been corrected.

  • 17 March 2022

    A Correction to this paper has been published: https://doi.org/10.1007/s11277-022-09574-5

Abbreviations

WSN:

Wireless sensors network

DoS:

Denial-of-Service

NS2:

Network Simulator2

T-MAC:

Time out-medium access control

FIS:

Fuzzy inference system

ANFIS:

Adaptive neuro-fuzzy inference system

IDS:

Intrusion Detection System

GW:

Gateway

NN:

Neural network

ECC:

Elliptic Curve Cryptography

LM:

Levenberg Marquardt

GWO:

Grey Wolf Optimizer

LA:

Lion Algorithm

PSO:

Particle Swarm Optimization

WOA:

Whale Optimization Algorithm

FPR:

False Positive Rate

FNR:

False Negative Rate

FDR:

False Discovery Rate

NPV:

Net Predictive Value

MCC:

Mathews Correlation Coefficient

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Authors and Affiliations

  1. St. Xavier’s Catholic College of Engineering, Nagercoil, India

    Sobini X. Pushpa

  2. Easwari Engineering College, Chennai, India

    S. Kanaga Suba Raja

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  1. Sobini X. Pushpa
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  2. S. Kanaga Suba Raja
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Contributions

SXP conceptualized and designed the study, reviewed identified articles to determine if they met defined study inclusion and exclusion criteria, critically reviewed the manuscript, and approved the final manuscript as submitted. SKR reviewed identified articles to determine if they met defined study inclusion and exclusion criteria, critically reviewed the manuscript, and approved the final manuscript as submitted. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

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Correspondence to Sobini X. Pushpa.

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The original version of this article was revised: In the original version of this article the affiliation details for authors Sobini X. Pushpa and S. Kanaga Suba Raja were incorrectly assigned. The original article has been corrected.

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Pushpa, S.X., Raja, S.K.S. Elliptic Curve Cryptography Based Authentication Protocol Enabled with Optimized Neural Network Based DoS Mitigation. Wireless Pers Commun 124, 1–25 (2022). https://doi.org/10.1007/s11277-021-08902-5

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