Abstract
This paper introduces a model for the authentication of large-scale images. The crucial element of the proposed model is the optimized Pulse Coupled Neural Network. This neural network generates position matrices based on which the embedding of authentication data into cover images is applied. Emphasis is placed on the minimalization of the stego image entropy change. Stego image entropy is consequently compared with the reference entropy of the cover image. The security of the suggested solution is granted by the neural network weights initialized with a steganographic key and by the encryption of accompanying steganographic data using the AES-256 algorithm. The integrity of the images is verified through the SHA-256 hash function. The integration of the accompanying and authentication data directly into the stego image and the authentication of the large images are the main contributions of the work.
Keywords
Cite this article
@article{cai-6662,
author = {Radoslav Forgáč and Miloš Očkay and Martin Javurek and Bianca Badidová},
title = {Steganography Approach to Image Authentication Using Pulse Coupled Neural Network},
journal = {Computing and Informatics},
volume = {42},
number = {3},
pages = {591--614},
year = {2023},
issn = {1335-9150},
doi = {10.31577/cai_2023_3_591}
}
TY - JOUR AU - Radoslav Forgáč AU - Miloš Očkay AU - Martin Javurek AU - Bianca Badidová TI - Steganography Approach to Image Authentication Using Pulse Coupled Neural Network JO - Computing and Informatics VL - 42 IS - 3 SP - 591 EP - 614 PY - 2023 SN - 1335-9150 DO - 10.31577/cai_2023_3_591 UR - https://doi.org/10.31577/cai_2023_3_591 KW - Image steganography KW - pulse coupled neural network KW - position matrix KW - image authentication ER -
Forgáč, R., Očkay, M., Javurek, M., & Badidová, B. (2023). Steganography Approach to Image Authentication Using Pulse Coupled Neural Network. Computing and Informatics, 42(3), 591–614. https://doi.org/10.31577/cai_2023_3_591