A novel image gravity transform based on least significant bit in image steganography

Mehdi Nikpour, Mohammad Taghi Kheirabadi and Ali Nodehi

Mathematics and Computers in Simulation (MATCOM), 2025, vol. 234, issue C, 396-418

Abstract: Information transmission technology has been developing rapidly in recent years, and high-quality and safe information transmission is one of the major challenges in today’s world. Steganography is a safe data transmission technique in which the data is embedded and hidden in a media content before sending it to the network. Text-in-image steganography is one of the important types of steganography that has various applications such as military, research and data mining. Designing an algorithm with high security and accurate retrieval of hidden data is one of the main challenges in text-in-image steganography. Hence, In this paper, a new efficient text-in-image steganography algorithm is proposed to enhance the security of hidden data and accuracy of data retrieval. This algorithm is composed of two components including data hiding and data retrieval. In the first component, the original data is hidden in the original Image and generate the stegano image. To this end, the algorithm of “finding the best non-uniform locations” (FBNL) is introduced. in addition the original text is encrypted by IGT algorithm. After that, the encrypted text is hidden in the best non-uniform location of image that founded by FBNL. The second component is executed when the original data is needed. in the start of this component, the FBNL algorithm runs and find the best non-uniform location and the inverse IGT (IIGT) algorithm uses this locations and recovers the original data. For evaluation, several datasets is employed for images including Cifar, Mnist, Pascal and LFW. In addition, the text data is retrieved from UCI dataset. The evaluation results show that the proposed algorithm has an improvement between 4.6 and 58.4 percent in terms of quality, error, security and time compared to other investigated algorithms in different scenarios.

Keywords: Steganography; LSB algorithm; Feature extraction; Image Gravity Transform (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475425000849
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:234:y:2025:i:c:p:396-418

DOI: 10.1016/j.matcom.2025.03.010

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().