Multistage Encryption of Mammogram Images Using Fractional Fourier Transform and 3D Chaotic Map
- DOI
- 10.2991/978-94-6463-314-6_24How to use a DOI?
- Keywords
- Chaotic encryption; FRFT; Information entropy; Correlation coefficients; Cyberattack
- Abstract
Transmission of biomedical images over long distance is very important for various applications like telemedicine and distant consultation with health experts. Many of these images carry confidential information and need to be highly secured before transmission. For the purpose of secured transmission, images must be encrypted. Hence, an efficient technique for secured communication of biomedical images is proposed in this communication, which is applicable equally for all types of images. In this communication, the algorithm is applied on mammogram images for detection of breast cancer. Security of transmitted images is enhanced by application of Fractional Fourier Transform (FRFT) and 3D Rabinovich Chaotic map. The algorithm shows satisfactory result for applications where image data are to be transmitted in highly secured way.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Banhi Das AU - Arijit Saha AU - Somali Sikder PY - 2023 DA - 2023/12/21 TI - Multistage Encryption of Mammogram Images Using Fractional Fourier Transform and 3D Chaotic Map BT - Proceedings of the International e-Conference on Advances in Computer Engineering and Communication Systems (ICACECS 2023) PB - Atlantis Press SP - 239 EP - 248 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-314-6_24 DO - 10.2991/978-94-6463-314-6_24 ID - Das2023 ER -