Modified Least Significant Bit Algorithm Applied in Digital Image Signature
Abstract
Purpose – This study aims to improve the embedding process and the integration of an additional layer of security to enhance the overall security of the based Least Significant Bit Algorithm.
Method – The study incorporated the use of NTRUEncrypt for the encryption of the plaintext message, and a randomized embedding technique by generating random pixel locations based on the Lorenz Chaos System. This was assessed using histogram analysis to show the difference between the original and the stego-image, Mean Squared Error (MSE), and Peak signal-to-noise ratio (PSNR).
Results – The modification has been evaluated using a histogram along with the result of its PSNR and MSE, at which the modified least significant bit algorithm obtains the highest PSNR score of 77.078% and the lowest MSE score of 0.0012% for the 512x512 image size, which resulted in a less distorted image and better quality of the image compared to the original base LSB.
Conclusion – The modification of the least significant bit algorithm successfully implemented a randomized embedding process through the Lorenz System and encrypted the secret message through NTRUEncrypt before embedding to further secure the message inside the image. Image distortion was also lessened as tested from the different sizes of images, which were tested through the PSNR and MSE metrics.
Recommendations – The study suggests the implication of machine learning algorithms in generating key pixel locations for data embedding and the use of text compression algorithms to reduce the size of the embedded secret message.
Research Implications – This study is a significant resource for future researchers interested in exploring literature on image steganography and secure communication. Thus, it introduces a novel approach by integrating lattice-based encryption and chaos systems, thereby enhancing secure communication through digital image steganography.
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