Toward Resisting Black-Box Attacks: A Robust Coverless Image Steganography Based on Hierarchical CID and Dual SIFT

Laijin Meng, Xinghao Jiang, Qiang Xu, Zhongjie Mi, Shijie Hou, Tanfeng Sun

Abstract: Coverless image steganography (CIS) can completely resist steganalysis algorithms as it does not modify the carriers. However, most existing CIS methods overlook the diversity of generated hash sequences, which directly impacts the practical maximum capacity and difficulty of constructing the index structure. Moreover, CIS methods typically consider robustness only under known parameters. In security, some methods require the transmission of auxiliary information along with stego images, while others reuse fixed images in the dataset, which raises potential suspicion from attackers. To address the above issues, a robust CIS method towards resisting black-box attacks is proposed. The normalized average of keypoint descriptor features is calculated by Scale-Invariant Feature Transform (SIFT) to construct the hierarchical coverless image dataset (CID). Subsequently, the mapping table between hash sequences and images in CID is established to accomplish secret information hiding and extraction. Experimental results demonstrate that the proposed CIS method achieves a higher capacity and stronger robustness than the state-of-the-art CIS methods. Notably, it is the first time to consider robustness against black-box and mixed attacks in CIS methods, making it more applicable to real-world scenarios.

External IDs:doi:10.1109/tdsc.2025.3613525