WITHDRAWN: A hybrid population based incremental learning algorithm with Particle Swarm Optimization for general threshold Visual Cryptography schemes

Abstract

Abstract An effortless transfer of multimedia information over the Internet is achieved due to advances in the network’s technology. Commercial identifications, similarity maps, and numerous confidential data can be transferred over the Internet. When dealing with private videos and images, security challenges must be accounted for as hackers steal information by exploiting the weak links across communication networks. There has been the development of numerous schemes for the management of the security challenges of private images and videos. The encryption of a secret image onto n shares, wherein all participants can hold one or more shares, is known as the Visual Cryptography (VC) scheme. In the probabilistic VC scheme, the secret black pixels are reconstructed incompletely thus, the display quality obtained is not consistent with human visual perception. To enhance the display quality, it is required to optimize the threshold VCS. In this work, meta heuristic algorithms, Particle Swarm Optimization (PSO), and Population-Based Incremental Learning (PBIL) are modified to optimize the VCS threshold. PSO’s abilities like simplicity, convergence speed, and optimum global searches, have made it the most frequently-employed evolutionary variant among hybrid techniques. Substitution of a population’s individuals with a set of their statistics forms the basis of the concept behind the PBIL algorithm. Proposal for a hybrid Population-Based Incremental Learning algorithm with Particle Swarm Optimization (PBIL-PSO) has been provided in this work.