A robust image-based cryptology scheme based on cellular nonlinear network and local image descriptors. Issue 5 (2nd September 2020) - Dehshibi, Mohammad Mahdi; Shanbehzadeh, Jamshid; Pedram, Mir Mohsen
Abstract : Cellular nonlinear network (CNN) provides an infrastructure for cellular automata to have not only an initial state but an input which has a local memory in each cell with much more complexity. This property has many applications which we have investigated it in proposing a robust cryptology scheme. This scheme consists of a cryptography and steganography sub-module in which a 3D CNN is designed to produce a chaotic map as the kernel of the system to preserve confidentiality and data integrity in cryptology. Our contributions are three-fold including (1) a feature descriptor is applied to the cover image to form the secret key while conventional methods use a predefined key, (2) a 3D CNN is used to make a chaotic map for making cipher from the visual message, and (3) the proposed CNN is also used to make a dynamic k -least significant bit steganography. Conducted experiments on 25 standard images prove the effectiveness of the proposed cryptology scheme in terms of security, visual, and complexity analysis.