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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
