A Hybrid Visual Cryptography Method using Sigmoid Function for Security Enhancement in Gray Scale Images (Indian Journal of Artificial Intelligence and Neural Networking (IJAINN), 2023)
Visual encryption technology becomes the latest research area in which a lot of scopes persist. Presently such a particular cryptosystem procedure is now used by numerous other countries around the world for the private transmission of formal records, financial documents, content visuals, digital voting, and so on. Visualization Cryptographic algorithms one of the protected methods of transferring pictures online. The main benefit of image encryption has been that it disguises peripheral vision with encrypt data secret data with no computation usually needed. In this work a hybrid visual cryptography method using a sigmoid function (HVMSF) for enhancing the security in gray images. HVMSF strategy utilizes a chaos framework to scramble pixel values as well as blocks while using the Modified Arnold Cat Map method (MACM) as well as the Henon Map method (HMM). The methodology includes a confusion procedure wherein the location of each image pixel is shuffled by utilizing MACM. The shuffling of image pixel leads to the creation of a subset pixel which will be protected for transmitting. This proposed HVMSF mainly tries to overcome the limitation of the previous approaches by applying sigmoid function in image feature space for contrast enhancement throughout the consequent source images. The experimental outcomes precisely show that the suggested strategy can further give additional effectiveness to ensure the protection of transmitting information out over previous techniques.