# Usage of analytic hierarchy process for steganographic inserts detection in images

## TL;DR

This paper introduces a steganography detection method using analytic hierarchy process to analyze bit layers in images, effectively identifying hidden messages even at low embedding rates.

## Contribution

It applies the analytic hierarchy process to steganography detection, providing a novel approach to identify embedded messages by analyzing bit layers and their hierarchies.

## Key findings

- Effective detection at embedding rates below 10%
- Accurate localization of hidden messages within five pixels
- Outperforms traditional statistical detection methods

## Abstract

This article presents the method of steganography detection, which is formed by replacing the least significant bit (LSB). Detection is performed by dividing the image into layers and making an analysis of zero-layer of adjacent bits for every bit. First-layer and second-layer are analyzed too. Hierarchies analysis method is used for making decision if current bit is changed. Weighting coefficients as part of the analytic hierarchy process are formed on the values of bits. Then a matrix of corrupted pixels is generated. Visualization of matrix with corrupted pixels allows to determine size, location and presence of the embedded message. Computer experiment was performed. Message was embedded in a bounded rectangular area of the image. This method demonstrated efficiency even at low filling container, less than 10\%. Widespread statistical methods are unable to detect this steganographic insert. The location and size of the embedded message can be determined with an error which is not exceeding to five pixels.