Lamport Blum Shub Signcryptive Extreme Learning Machine for Secure Transmission of Digital Images

Abstract

Image transmission refers to sending or transferring digital images from one location to another, typically over a network or communication channel across various domains, including telecommunications, multimedia messaging, surveillance systems, medical imaging, remote sensing, etc. However, with growing popularity of digital skills, ensuring safety and integrity of transmitted images has become a significant concern. For increasing security, Machine learning and cryptographic techniques have been discussed. Nevertheless, confidentiality during image transmission faces major challenges. Proposed Lamport Blum ShubSigncryptive Extreme Learning (LBSSEL) Method is introduced for secured image transmission with minimal time consumption. The Extreme Learning machine comprises different layers. Several natural images gathered as of dataset. The input layer receives these images for secure transmission. The proposed cryptographic method performs key generation, signcryption, as well as unsigncryption. Lamport One-Time Digital signature method applied in first hidden layer to generate key pairs. Signcryption carried out in second hidden layer which includes encryption and digital signature. For secured transmission, an encrypted image (i.e., cipher image) as well as signature broadcast to receiver to preserve input image. In third hidden layer, unsigncryption process carried out for receiving original image by authorized users through signature verification and decryption. Finally, confidentiality is improved during image transmission at the output layer. Simulation estimated with dissimilar factors. Outcomes of LBSSSEL model in terms of achieving maximum PSNR, confidentiality during transmission, with minimal time consumption when compared with existing approaches.