Original Article
Enhancing Financial Security: Chaotic Map Integration with Biometric Data
Year: 2024 | Month: June | Volume 69 | Issue 2
1.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 Scholar2.Dunstone, T. and Yager, N. (Eds.). 2009. Biometric system and data analysis: Design, evaluation, and data mining. Boston, MA: Springer US.
View at Google Scholar3.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 Scholar4.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 Scholar5.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 Scholar6.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 Scholar7.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 Scholar8.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 Scholar9.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 Scholar10.Kindt, E.J. 2016. Privacy and data protection issues of biometric applications (Vol. 1). New York: Springer.
View at Google Scholar11.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 Scholar12.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 Scholar13.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 Scholar14.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 Scholar15.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 Scholar16.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 Scholar17.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 Scholar18.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 Scholar19.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



