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2020-06-22
Sreenivasan, Medha, Sidhardhan, Anargh, Priya, Varnitha Meera, V., Thanikaiselvan.  2019.  5D Combined Chaotic System for Image Encryption with DNA Encoding and Scrambling. 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN). :1–6.
The objective of this paper was to propose a 5D combined chaotic system used for image encryption by scrambling and DNA encryption. The initial chaotic values were calculated with a set of equations. The chaotic sequences were used for pixel scrambling, bit scrambling, DNA encryption and DNA complementary function. The average of NPCR, UACI and entropy values of the 6 images used for testing were 99.61, 33.51 and 7.997 respectively. The correlation values obtained for the encrypted image were much lower than the corresponding original image. The histogram of the encrypted image was flat. Based on the theoretical results from the tests performed on the proposed system it can be concluded that the system is suited for practical applications, since it offers high security.
2017-12-27
Shyamala, N., Anusudha, K..  2017.  Reversible Chaotic Encryption Techniques For Images. 2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN). :1–5.

Image encryption takes been used by armies and governments to help top-secret communication. Nowadays, this one is frequently used for guarding info among various civilian systems. To perform secure image encryption by means of various chaotic maps, in such system a legal party may perhaps decrypt the image with the support of encryption key. This reversible chaotic encryption technique makes use of Arnold's cat map, in which pixel shuffling offers mystifying the image pixels based on the number of iterations decided by the authorized image owner. This is followed by other chaotic encryption techniques such as Logistic map and Tent map, which ensures secure image encryption. The simulation result shows the planned system achieves better NPCR, UACI, MSE and PSNR respectively.