Introducing a New Evaluation Criteria for EMD-Base Steganography Method

TL;DR

This paper proposes a new evaluation criterion for EMD-based steganography methods that effectively balances security and capacity by measuring embedding efficiency, enabling better comparison of different techniques.

Contribution

It introduces a novel embedding efficiency formula and an upper bound for evaluating EMD-based steganography methods, improving comparison accuracy.

Findings

The proposed formula better reflects performance when multiple pixel changes occur.

An upper bound for embedding efficiency was derived for each capacity.

The new criterion enhances the comparison of steganography methods.

Abstract

Steganography is a technique to hide the presence of secret communication. When one of the communication elements is under the influence of the enemy, it can be used. The main measure to evaluate steganography methods in a certain capacity is security. Therefore, in a certain capacity, reducing the amount of changes in the cover media, creates a higher embedding efficiency and thus more security of an steganography method. Mostly, security and capacity are in conflict with each other, the increase of one lead to the decrease of the other. The presence of a single criterion that represents security and capacity at the same time be useful in comparing steganography methods. EMD and the relevant methods are a group of steganography techniques, which optimize the amount of changes resulting from embedding (security). The present paper is aimed to provide an evaluation criterion for this group of steganography methods. In this study, after a general review and comparison of EMD-based steganography techniques, we present a method to compare them exactly, from the perspective of embedding efficiency. First, a formula is presented to determine the value of embedding efficiency, which indicates the effect of one or more changes on one or more pixels. The results demonstrate that the proposed embedding efficiency formula shows the performance of the methods better when several changes are made on a pixel compared to the existing criteria. In the second step, we have obtained an upper bound, which determines the best efficiency for each certain capacity. Finally, based on the introduced bound, another evaluation criterion for a better comparison of the methods is presented.