High‐quality steganography scheme using hybrid edge detector and Vernam algorithm based on hybrid fuzzy neural network

• Published in: Concurrency and computation 2021-12, Vol.33 (24), p.n/a
• Main Authors: Dhawan, Sachin, Gupta, Rashmi
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial neural networks; Communication; Data communication; Fuzzy logic; Image enhancement; Image quality; Innovations; KL divergence; mean square error; neural network; Neural networks; PSNR; Security; Sobel and Kirsch edge detector; Steganography; structural similarity index; Vernam algorithm
• ISSN: 1532-0626; 1532-0634
• DOI: 10.1002/cpe.6448

Summary There has been a developing extension in the utilization of steganography, because of the advancement in utilizing web innovation and interactive media innovation. Subsequently, these days, the data are not made sure about adequately while transmitting it over the system. Data are the most significant resource for the current electronic communication framework. Thus the data security has played a significant job to give protection from unapproved people. Steganography is the technique that provides the solution for this challenge. This article proposes a novel type of steganography strategy in which it uses the hybrid algorithm for higher security and a hybrid fuzzy neural network is utilized for the good quality of stego images. For higher security, this article utilizes the Sobel and Kirsch edge identifier and then the Vernam algorithm utilized for encrypting the secret image. Thereafter this article utilizes the combination of fuzzy logic and neural network for enhancing the quality of stego images. There are various advantages of this technique that it can be utilized in various areas, for example, confidential data communication in the defense sector, medical, electronic governance, banking, communication, and so on.