A Secure Image Steganography Using Shark Smell Optimization and Edge Detection Technique

Abstract

The steganographic system provides premium secrecy and ability of conserving the secret information from gaining stalked or cracked. The suggested method consists of five phases which are masking and divided image, edge detection, apply shark smell optimization (SSO), embedding and extraction. This paper concentrated on three significant basic parts which are payload, quality, and security also introduces a new steganography method through using edge detection algorithm and SSO. The process of concealment is carried out through the following steps: Firstly, to promote the hiding ability and to realize altitude standard of secrecy the secret message is separated into four parts and the cover image is masked and divided into four sections, then the edge detection algorithm and SSO is performed on each section respectively. Edge prospectors were utilized to produce edge pixels in every section to hide secret message and attain the best payload. To increase security, the shark smell optimization is used to select the best pixels among edge pixels based on its nature in motion, then reflect these best pixels on original cover image. Finally the secret message bits are hidden in the selected edge best pixels by using lest significant bit technique. The experimental out comes appreciated utilizing several image fitness appreciation fashion, it displays best hiding ability, achieve higher image quality with least standard of deformation and provide altitude standard of secrecy, also the results shows that the suggested method exceeds previous approaches in term of the PSNSR and MSE, additionally demonstrate that the secret information cannot be retrieved from Stego image without knowing the algorithms and the values of parameters used.