Anti-Forgery based on N-Round Crypto-Steganographic Algorithms

The paper proposes a robust crypto-steganography approach that secures the data without affecting it and efficient anti-forgery tool. The proposed approach consists of main three security levels with n-round sub-levels. The hybridization of crypto-chaos based tools with various data hiding tools is performed perfectly. The paper carried out several simulation experiments using multi dataset (Math work, Yolov8 and others) to evaluate the proposed scenarios and find integration of these techniques that provides the best security performance without affecting the data. The best simulation experiments that provided the best data security performance were the integration between 2D Logistic map, SVD, and Baker Map, respectively. The proposed steganography performs better than the recent published related works and compared with the deep learning based steganography. The proposed combined system provided the better simulation results for image security. The simulation results indicated a perfect match between the original message and the decryption original message after applying the system. The results also indicated that there was no effect on the data and no loss of data. As clarified in the results, the proposed hybridization approach can be considered a perfect tool to combat the forgery and tampering attacks on the classified data and immune the data transferring over the various networks.