Removing Hidden Information by Geometrical Perturbation in Frequency Domain

Lin He, Bingwen Feng, Zecheng Peng, Bing Chen, Zhihua Xia, Wei Lu

Abstract: The risk of malicious exploitation of advanced image steganography necessitates the removal of hidden information from images. However, it is crucial to preserve the visual quality of the images undergoing processed. This paper suggests a geometrical attack in frequency domain (GAF) to address this challenge. GAF employs a thin plate spline (TPS) to slightly geometrically perturb the frequency components of the stego image. It incorporates a channel weight estimator and a frequency jammer. The channel weight estimator assigns perturbation strengths to each DCT channel, while the frequency jammer performs the TPS transform on the DCT channels using the assigned perturbation strengths. Experimental results demonstrate that the proposed approach effectively hinders secret image recovery with a little distortion to the stego images. Furthermore, it well preserves the visual quality of clear images that do not contain secret information.