Multimedia Data Protection Using Hybridized Crystal Payload Algorithm With Chicken Swarm Optimization

Abstract

This research consists of three phase. The first model includes a crystal payload encryption method watermarking scheme and an attack-free encryption scheme called international data encryption algorithm (IDEA). The second model is a binary grey scale image in chicken swarm optimization (CSO) applied to copyright production parameter optimized swarm intelligence domain-based approach, which is compared to conventional approaches. The work performance has been evaluated for conventional machine learning approach using MATLAB. The simulation results show that proposed hybridized crystal payload algorithm with chicken swarm optimization (HCPECSO) scheme achieves a high copyright production with the lowest mean square error values and highest peak signal noise ration when compared with the existing approaches schemes like machine learning SVM, logistic regression, and neural network. The proposed HCPECSO attained less processing time of 32.33s and processing cost compared to existing schemes.