Ratnavelu, Kurunathan and Kalpana, M. and Balasubramaniam, P. and Wong, K. and Paramesran, Raveendran (2017) Image encryption method based on chaotic fuzzy cellular neural networks. Signal Processing, 140. pp. 87-96. ISSN 0165-1684, DOI https://doi.org/10.1016/j.sigpro.2017.05.002.
Full text not available from this repository.Abstract
In this work, an image encryption method is proposed based on fuzzy cellular neural network (FCNN). First, the shortcomings of FCNN in encrypting image are identified, and the FCNN model is then modified to address these shortcomings. Specifically, a theoretical framework is developed to identify the values of the parameters of FCNN to generate chaotic signals, which are in turn utilized to encrypt the image. The encryption method is designed where an encrypted pixel is generated based on the corresponding plaintext pixel together with the neighbouring encrypted pixels. The proposed method has a key sensitivity in the order of 10−10 to achieve adequate security robustness. Further evaluations on standard test images verified and confirmed that the proposed encryption method is robust against plaintext-only (i.e., brutal force) and chosen-plaintext attacks.
| Item Type: | Article |
|---|---|
| Funders: | Fundamental Research Grant Scheme (FRGS) MoHE Grant (FP051-2016), University of Malaya HIR under Project UM.C/625/1/HIR/MOHE/ENG/42 |
| Uncontrolled Keywords: | Chaos; Encryption; Leakage delay; Fuzzy cellular neural network |
| Subjects: | Q Science > QA Mathematics T Technology > T Technology (General) |
| Divisions: | Faculty of Engineering Faculty of Science > Institute of Mathematical Sciences |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 20 Jul 2017 08:24 |
| Last Modified: | 20 Sep 2019 08:30 |
| URI: | http://eprints.um.edu.my/id/eprint/17550 |
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