Manuscript Number : SHISRRJ247242

Enhancing Web Security

Authors(2) :-Dr. K. Shanmugam, Gangireddy Jyoshna

In the digital banking era, securing sensitive data is paramount. This paper introduces a unique image method using chaos-driven neural networks to bolster banking security. By blending chaotic systems and neural networks, encryption is fortified. Commencing with chaotic sequence extraction via advanced functions, cryptographic keys introduce unpredictability. Neural networks then adjust parameters based on input images, enhancing defense against attacks. This fusion yields a robust mechanism for banking data, resilient against attacks and adaptable to emerging threats. Experimental results validate its efficacy and efficiency, positioning it as a promising solution.

Authors and Affiliations

Dr. K. Shanmugam
Assistant Professor, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India
Gangireddy Jyoshna
Post Graduate, Department of MCA, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India

Python, Encryption, Chaotic dynamics, OpenCV, Image processing, Security, Banking, Authentication Decryption, Neural networks.

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  2. Erkan, U., Toktas, A., Enginoğlu, S. et al. An image encryption scheme based on chaotic logarithmic map and key generation using deep CNN. Multimed Tools Appl 81, 7365– 7391 (2022).
  3. L Chen, Y. Hao, T. Huang et al., Chaos in fractional-orde

Publication Details

Published in : Volume 7 | Issue 2 | March-April 2024
Date of Publication : 2024-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 238-244
Manuscript Number : SHISRRJ247242
Publisher : Shauryam Research Institute

ISSN : 2581-6306

Cite This Article :

Dr. K. Shanmugam, Gangireddy Jyoshna, "Enhancing Web Security", Shodhshauryam, International Scientific Refereed Research Journal (SHISRRJ), ISSN : 2581-6306, Volume 7, Issue 2, pp.238-244, March-April.2024
URL : https://shisrrj.com/SHISRRJ247242

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