A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques
This is the code implementation for the article: A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques
With remarkable information technology development, information security has become a major concern in the communication environment, where security must be performed for the multimedia messages exchanged between the sender and the intended recipient. Digital multimedia steganography techniques have been developed to attain a security for covert communication and secure data. This paper proposes an approach for image steganography using the Least Significant Bit Substitution (LSB) and Nature-Inspired Harris Hawks Optimization (HHO) algorithm for efficient concealing of the secret data inside a cover image; thus providing high confidentiality. The HHO based data encoding operation uses the PSNR visual quality metric as an objective function. The objective function is used to determine the ideal encoding vector to convert the secret message to its encoded form. The proposed approach performs better than other state-of-the-art methods in terms of standard measures of visual quality with maintaining high embedding capacity. Comparisons with existing LSB or multi-directional PVD embedding methods demonstrate that the proposed method has more optimized and higher embedding capacity with maintaining visual quality. Besides, the proposed approach achieves high security against statistical StegoExpose analysis, ALASKA2 deep learning steganalysis, and image processing attacks.
Data security
Data hiding
Image steganography
Optimization algorithms
Metaheuristic
Hameed, M.A., Abdel-Aleem, O.A. & Hassaballah, M. A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques. J Ambient Intell Human Comput (2022). https://doi.org/10.1007/s12652-022-04366-y
@article{hameed2022secure,
title={A secure data hiding approach based on least-significant-bit and nature-inspired optimization techniques},
author={Hameed, Mohamed Abdel and Abdel-Aleem, Omar A and Hassaballah, M},
journal={Journal of Ambient Intelligence and Humanized Computing},
pages={1--19},
year={2022},
publisher={Springer}
}
Note: Unfortunately, this code is published late as compared to the first time I wrote it, so if there are any missing files, code segments, or errors, please feel free to open an issue.