A new image encryption algorithm based on hyper-chaos
By Tiegang Gao, Zengqiang Chen. 2008
328 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Mathematical Physics, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/4fcbe0b576eb5e35918d2e845a4031ffd264a316
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Zhongyun Hua
- Yicong Zhou
- Chunhua Wang
- Hua Chen
- Yueping Li
- Xing-yuan Wang
- C. L. Philip Chen
- Chi-Man Pun
In Mathematical Physics
- Zhongyun Hua
- Yicong Zhou
- Xing-yuan Wang
- Chunhua Wang
- Hua Chen
- Yueping Li
- C. L. Philip Chen
- Chi-Man Pun
In Statistical and Nonlinear Physics
- Zhongyun Hua
- Yicong Zhou
- Xing-yuan Wang
- Chunhua Wang
- Hua Chen
- Yueping Li
- Premkumar Natarajan
- Chi-Man Pun
Citations in the corpus
- Cryptanalysis of a new image encryption algorithm based on hyper-chaos (2008, background): “Although a number of them have been cryptanalyzed, many others have not been effectively attacked like the one in [8].”
- Synchronization of an Inertial Neural Network With Time-Varying Delays and Its Application to Secure Communication (2018, background): “In [23], an encryption algorithm for color images using bitlevel permutation and Chen’s chaotic system was described.”
- A novel chaotic block image encryption algorithm based on dynamic random growth technique (2015, background): “Some proposed image encryption schemes only do XOR operation on the original or scrambling images [5–8].”
- A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation (2017, methodology): “In [34], Gao and Chen proposed a hyperchaos-based image encryption algorithm using pixel-level permutation.”
- Cascade Chaotic System With Applications (2015, background): “D chaotic maps, HD chaotic maps usually have better chaotic performance and their chaotic orbits are more difficult to predict [17].”
- Shannon Entropy based Randomness Measurement and Test for Image Encryption (2011, methodology): “Image randomness can be measured using a variety of methods, such as histogram analysis [6,12,16,22,28,29,35,37,40,42,54,55,57,60,63,64], global Shannon entropy measure [6,12,42,55,64,66], adjacent pixel correlations [6,12,16,35,42,57,64,66].”