Embedding Change Estimation for Universal Steganalysis using 3-way Tensor Model - Arunvinodh, C; Poonkuntran, S (International Journal of Computer Sciences and Engineering, 2025)
This paper proposes a novel Universal Steganalysis framework which can be applied for spatial domain and JPEG Domain Steganography algorithms. The objective is to develop a steganalysis algorithm which has to identify any distribution (uniform or non-uniform) of stego-payloads. The framework proposed uses a 3-way tensor model to extract the image features which is important for estimating the embedded change irrespective of domain. To obtain the accurate results and to analyze the error, 360 degree bit change estimation is done. The experimental results evaluated on 3000 images which shows a good detection rate in both domains and a reasonable false acceptance rate and false rejection rate based on the pay load when tested with most of the steganography algorithms.