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Attack detection and securer data transmission in cognitive radio networks using BMHHO-ENN and SHA2-RSA

  • Foundation, algebraic, and analytical methods in soft computing
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Abstract

The attention of the researchers has highly turned towards the Cognitive Radio Networks (CRN) due to its high efficiency and throughput performance. In comparison with the conventional radio environment, the Cognitive Radio (CR) has numerous security threats as it is flexible together with functions on the wireless network. Attributable to the inherent nature of the technology, the security susceptibility in CR technology, therefore, it is vital to guarantee system security in CRN. So, this paper proposes an optimal Neural Network (NN) model explicitly Brownian movement based Harris Hawks Optimization for Elman Neural Network (BMHHO-ENN) for attaining a secure CRN. Additionally, this paper also proposes Secure Hash Algorithm 2-Rivest Shamir Adlemans (SHA2-RSA) to render safe data communication. Initially, the Amplitudes Modulations signal of PU is deemed as an input. Then, the energy together with Cyclo Stationary features of the inputted signal are extracted utilizing the mathematical model. Aimed at Attack Detection (AD), the extracted features are fed to the proposed BMHHO-ENN. BMHHO-ENN classifies the inputted signal into ‘4’ disparate sorts of attack, and if the signal is not attacked by the intruder, it renders the classification outcomes as “normal”. Lastly, if it is not attacked, then the SHA2-RSA algorithm encrypts that classified normal data and stores it in the cloud for the receiver-side data access to render security. The proposed methods’ outcomes are examined as well as contrasted with the other prevailing methods to show the proposed work’s efficiency for AD along with the data’s security.

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Data availability

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

Abbreviations

CRN:

Cognitive radio networks

CR:

Cognitive radio

NN:

Neural network

SHA2-RSA:

Secure Hash Algorithm 2-Rivest Shamir Adlemans

AM:

Amplitudes modulations

CS:

Cyclo stationary

AD:

Attack detection

HHO:

Harris Hawk Optimization

MAC:

Medium access control

BM:

Brownian movement

WC:

Wireless communication

SS:

Spectrum sensing

GABC:

Genetics artificial bee colonies

SDR:

Software-defined radio

SSM:

Spectrum sensing model

CSS:

Cooperative spectrums sensing

SSDF:

Spectrum sensing data falsification

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Acknowledgements

We thank the anonymous referees for their useful suggestions.

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Authors and Affiliations

  1. Electronics and Communication Engineering, National Engineering College, Anna University, Chennai, India

    K. J. Prasanna Venkatesan & S. Shanmughavel

Authors
  1. K. J. Prasanna Venkatesan
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  2. S. Shanmughavel
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by KJPV, SS. The first draft of the manuscript was written by KJPV and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to K. J. Prasanna Venkatesan.

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Venkatesan, K.J.P., Shanmughavel, S. Attack detection and securer data transmission in cognitive radio networks using BMHHO-ENN and SHA2-RSA. Soft Comput 26, 175–187 (2022). https://doi.org/10.1007/s00500-021-06462-1

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