Background: The necessity for data security is demanding in the digital age. The main technique for achieving data security is Steganography. The technique of camouflaging the secret object behind another cover object is known as Steganography. A novel, robust, high payload, and imperceptible image steganography approach using matrix inverse in the spatial domain are proposed in this manuscript. The basic idea is to devise a robust novel approach against various image processing attacks, like cropping, compression, filters, and noise.
Objectives: The study's objective is to develop a novel data-hiding approach that increases imperceptibility and payload capacity and is robust against various image processing attacks, like filters, compression, cropping, and noise.
Methods: The matrix inverse procedure is used for the insertion and extraction of data. The symmetry feature of the matrix inverse makes the task of insertion of data simple and efficient. It also increases the hiding capacity while maintaining a finer level of imperceptibility and robustness. MATLAB is used for the implementation of the new technique and results analysis.
Results: The proposed method's robustness has been analyzed against image processing assaults such as the inclusion of various noises, cropping, a variety of filters, and compression assaults. The imperceptibility of the approach has been tested successfully using PSNR, BER, and NCC metrics. The proposed method has been compared with the other two techniques. The experimental and comparison results depict that the proposed approach provides high hiding capacity, finer robustness, and imperceptibility.
Conclusion: A novel, robust and imperceptible approach has been developed in this manuscript. The proposed method has been compared with the methods developed by Jung & Yoo and Joshi & Gill. The experimental findings show that the proposed technique offers better resilience, payload capacity, and finer imperceptibility.