Prabhudeva S.

Work place: JNNCE/MCA, Shivamogga, 577204, Karnataka, India

E-mail: pdshirematt@gmail.com

Website: https://orcid.org/0000-0002-7720-3776

Research Interests:

Biography

Prof. Prabhudeva S. is working as a Professor and Director in the Department of Master of Computer Applications (MCA) at Jawaharlal Nehru New College of Engineering (JNNCE), Shivamogga, Karnataka, India. He received his Ph.D. degree in Reliability Engineering from IIT Bombay, India in 2010. Presently three research scholars are pursuing Ph.D. under his guidance. His research interests include Reliable and Security Modelling. He has published 22 papers in international journals and conferences. He has 18 years of research experience.

Author Articles
Two-Layer Security of Images Using Elliptic Curve Cryptography with Discrete Wavelet Transform

By Ganavi M. Prabhudeva S.

DOI: https://doi.org/10.5815/ijcnis.2023.02.03, Pub. Date: 8 Apr. 2023

Information security is an important part of the current interactive world. It is very much essential for the end-user to preserve the confidentiality and integrity of their sensitive data. As such, information encoding is significant to defend against access from the non-authorized user. This paper is presented with an aim to build a system with a fusion of Cryptography and Steganography methods for scrambling the input image and embed into a carrier media by enhancing the security level. Elliptic Curve Cryptography (ECC) is helpful in achieving high security with a smaller key size. In this paper, ECC with modification is used to encrypt and decrypt the input image. Carrier media is transformed into frequency bands by utilizing Discrete Wavelet Transform (DWT). The encrypted hash of the input is hidden in high-frequency bands of carrier media by the process of Least-Significant-Bit (LSB). This approach is successful to achieve data confidentiality along with data integrity. Data integrity is verified by using SHA-256. Simulation outcomes of this method have been analyzed by measuring performance metrics. This method enhances the security of images obtained with 82.7528db of PSNR, 0.0012 of MSE, and SSIM as 1 compared to other existing scrambling methods.

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