Year: 2025
Type: article
Abstract: In an era of rapidly evolving communication methods, the exchange of sensitive information— such as personal data, financial records, and proprietary business knowledge—has become increasingly vulnerable to interception and misuse. As a result, organizations must adopt robust security measures and encryption technologies to safeguard their communications and maintain trust with their stakeholders. Whether it's military, financial, medical, personal, etc.—sharing information over the Internet and social networks has become an urgent necessity that cannot be ignored. This is where the importance of steganography technology, which is concerned with maintaining the confidentiality of information by camouflaging it, comes into play. This technology, which is a unique process, allows us to hide a secret message inside another file, often an image known as a camouflaged image. After entering the secret information into that image, the resulting image is called a "stego image." The goal of this process is to not reveal the secret information contained in the original file, making it difficult or even impossible to distinguish between the original copy and the document containing the secret message. There are many ways to achieve this, the most prominent of which is the LSB technique, which relies on the least significant bit. However, despite its effectiveness, this method suffers from a major limitation, which is the small size of the stored. information. Therefore, in this research, we decided to adopt a method that combines secret information processing and LSB technology with the aim of increasing the size of the stored information while maintaining image quality and confidentiality. This pursuit of excellence truly demonstrates how important innovation is to protecting our privacy in today's connected world.
Source: Journal of Machine and Computing
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409183680