MODIFIED MULTI-LEVEL STEGANOGRAPHY TO ENHANCE DATA SECURITY

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Shadi Elshare
Nameer N EL Emam

Abstract

Data-hiding using steganography algorithm becomes an important technique to prevent unauthorized users to have access to a secret data.  In this paper, steganography algorithm has been constructed to hide a secret data in a gray and a color images, this algorithm is named deep hiding/extraction algorithm (DHEA) to modify multi-level steganography (MLS). The suggested hiding algorithm is based on modified least significant bit (MDLSB) to scatter data in a cover-image and it utilizes a number of levels; where each level perform hiding data on a gray image except the last level that applies a color image to keep secret data. Furthermore, proper randomization approach with two layers is implemented; the first layer uses random pixels selection for hiding a secret data at each level, while the second layer implements at the last level to move randomly from segment to the others. In addition, the proposed hiding algorithm implements an effective lossless image compression using DEFLATE algorithm to make it possible to hide data into a next level. Dynamic encryption algorithm based on Advanced Encryption Standard (AES) is applied at each level by changing cipher keys (Ck) from level to the next, this approach has been applied to increase the security and working against attackers. Soft computing using a meta-heuristic approach based on artificial bee colony (ABC) algorithm has been introduced to achieve smoothing on pixels of stego-image, this approach is effective to reduce the noise caused by a hidden large amount of data and to increase a stego-image quality on the last level. The experimental result demonstrates the effectiveness of the proposed algorithm with bee colony DHA-ABC to show high-performing to hide a large amount of data up to four bits per pixel (bpp) with high security in terms of hard extraction of a secret message and noise reduction of the stego-image. Moreover, using deep hiding with unlimited levels is promising to confuse attackers and to compress a deep sequence of images into one image.

Article Details

How to Cite
Elshare, S., & EL Emam, N. N. (2022). MODIFIED MULTI-LEVEL STEGANOGRAPHY TO ENHANCE DATA SECURITY. International Journal of Communication Networks and Information Security (IJCNIS), 10(3). https://doi.org/10.17762/ijcnis.v10i3.3614 (Original work published December 19, 2018)
Section
Research Articles
Author Biography

Nameer N EL Emam, Computer Science, Philadelphia University, Amman – Jordan, P. O. Box (1) Philadelphia, 19392 E-mail:Nemam@philadelphia.edu.jo,

Nameer N. EL-Emam has completed his PhD with honour 1997. He works as an assistant professor in the Computer Science Department at Basra University. In 1998, he joins the Department of Computer Science, Philadelphia University, as an assistant professor. and then he got an associate professor in 2010. Now he is a full professor at the same university, and he works as a chair of computer science department and the deputy dean of the faculty of Information Technology, Philadelphia University. His research interest includes Computer Simulation with an intelligent system, Parallel Algorithms, and Soft computing using Neural Network, GA, ACO, and PSO for many kinds of applications like Image Processing, Sound Processing, Fluid Flow, and Computer Security (Steganography).