Document Type

Journal Article

Publication Title

Indonesian Journal of Electrical Engineering and Computer Science

Volume

25

Issue

1

First Page

329

Last Page

338

Publisher

Institute of Advanced Engineering and Science

School

School of Engineering

Funders

Edith Cowan University

Comments

Abdali, N. M., & Hussain, Z. M. (2022). Reference-free differential histogram-correlative detection of steganography: Performance analysis. Indonesian Journal of Electrical Engineering and Computer Science, 25(1), 329-338.

https://doi.org/10.11591/ijeecs.v25.i1.pp329-338

Abstract

Recent research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which is needed in the classification process to detect tampering, reference-free steganalysis attracted attention. In recent work, an approach for least significant bit (LSB) steganalysis has been presented based on analyzing the derivatives of the histogram correlation. In this paper, we further examine this strategy for other steganographic methods. Detecting image tampering in the spatial domain, such as image steganography. It is found that the above approach could be applied successfully to other kinds of steganography with different orders of histogram-correlation derivatives. Also, the limits of the ratio stego-image to cover are considered, where very small ratios can escape this detection method unless modified.

DOI

10.11591/ijeecs.v25.i1.pp329-338

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Creative Commons Attribution-Share Alike 4.0 License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.

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