Original Article

Enhancing Financial Security: Chaotic Map Integration with Biometric Data

Year: 2024 | Month: June | Volume 69 | Issue 2

References (19)

Belazi, A., Abd El-Latif, A.A. and Belghith, S. 2016. A novel image encryption scheme based on substitutionpermutation network and chaos. Signal Processing, 128: 155-170.

View at Google Scholar

Dunstone, T. and Yager, N. (Eds.). 2009. Biometric system and data analysis: Design, evaluation, and data mining. Boston, MA: Springer US.

View at Google Scholar

Elkandoz, M.T. and Alexan, W. 2022. Image encryption based on a combination of multiple chaotic maps. Multimedia Tools and Applications, 81(18): 25497-25518.

View at Google Scholar

Essaid, M., Akharraz, I., Saaidi, A. and Mouhib, A. 2018. A new image encryption scheme based on confusion-diffusion using an enhanced skew tent map. Procedia Computer Science, 127: 539-548.

View at Google Scholar

Haddada, Lamia Rzouga, Bernadette Dorizzi, and Najoua Essoukri Ben Amara. 2017. Combined watermarking approach for securing biometric data.” Signal Processing: Image Communication, 55: 23-31.

View at Google Scholar

Hosny, K.M., Kamal, S.T. and Darwish, M.M. 2022. A color image encryption technique using block scrambling and chaos. Multimedia Tools and Applications, pp. 1-21.

View at Google Scholar

Hu, G. and Li, B. 2021. Coupling chaotic system based on unit transform and its applications in image encryption. Signal Processing, 178: 107790.

View at Google Scholar

Karmouni, H., Sayyouri, M. and Qjidaa, H. 2021. A novel image encryption method based on fractional discrete Meixner moments. Optics and Lasers in Engineering, 137: 106346.

View at Google Scholar

Kaur, G., Agarwal, R. and Patidar, V. 2022. Color image encryption system using combination of robust chaos and chaotic order fractional Hartley transformation. Journal of King Saud University-Computer and Information Sciences, 34(8): 5883-5897.

View at Google Scholar

Kindt, E.J. 2016. Privacy and data protection issues of biometric applications (Vol. 1). New York: Springer.

View at Google Scholar

Li, C., Lin, D. and Lü, J. 2017. Cryptanalyzing an imagescrambling encryption algorithm of pixel bits. IEEE Multi Media, 24(3): 64-71.

View at Google Scholar

Louzzani, N., Boukabou, A., Bahi, H. and Boussayoud, A. 2021. A novel chaos based generating function of the Chebyshev polynomials and its applications in image encryption. Chaos, Solitons & Fractals, 151: 111315.

View at Google Scholar

Ma, Y., Li, C. and Ou, B. 2020. Cryptanalysis of an image block encryption algorithm based on chaotic maps. Journal of Information Security and Applications, 54: 102566.

View at Google Scholar

Natgunanathan, I., Mehmood, A., Xiang, Y., Beliakov, G. and Yearwood, J. 2016. Protection of privacy in biometric data. IEEE Access, 4: 880-892.

View at Google Scholar

Sekar, J.G., Arun, C., Abilash, V.M., Aravindan, K., Barathiselvan, K. and Bharath, J. 2022. A modified chaotic image encryption scheme for color image using diagonal pixel confusion and diffusion method. In AIP Conference Proceedings (Vol. 2405, No. 1). AIP Publishing.

View at Google Scholar

Shahna, K.U. and Mohamed, A. 2020. A novel image encryption scheme using both pixel level and bit level permutation with chaotic map. Applied Soft Computing, 90: 106162.

View at Google Scholar

Sridevi, A., Sivaraman, R., Balasubramaniam, V., Sreenithi, Siva, J., Thanikaiselvan, V. and Rengarajan, A. 2022. On Chaos based duo confusion duo diffusion for colour images. Multimedia Tools and Applications, 81(12): 16987- 17014.

View at Google Scholar

Wang, X.Y. and Li, Z.M. 2019. A color image encryption algorithm based on Hopfield chaotic neural network. Optics and Lasers in Engineering, 115: 107-118.

View at Google Scholar

Ye, G. 2010. Image scrambling encryption algorithm of pixel bit based on chaos map. Pattern Recognition Letters, 31(5): 347-354.

View at Google Scholar

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