Image Steganography based on a Parameterized Canny Edge Detection Algorithm

TL;DR

This paper introduces a novel image steganography method that embeds data within Canny edge-detected pixels, using parameterized thresholds to enhance unpredictability and security against detection.

Contribution

It proposes a new steganography technique leveraging parameterized Canny edge detection to improve irrecoverability and concealment of hidden data.

Findings

Effective hiding of data within edge pixels of images.

Parameterization increases difficulty for steganalysis.

Simulation results demonstrate robustness of the method.

Abstract

Steganography is the science of hiding digital information in such a way that no one can suspect its existence. Unlike cryptography which may arouse suspicions, steganography is a stealthy method that enables data communication in total secrecy. Steganography has many requirements, the foremost one is irrecoverability which refers to how hard it is for someone apart from the original communicating parties to detect and recover the hidden data out of the secret communication. A good strategy to guaranteeirrecoverability is to cover the secret data not usinga trivial method based on a predictable algorithm, but using a specific random pattern based on a mathematical algorithm. This paper proposes an image steganography technique based on theCanny edge detection algorithm.It is designed to hide secret data into a digital image within the pixels that make up the boundaries of objects detected in the image. More specifically, bits of the secret data replace the three LSBs of every color channel of the pixels detected by the Canny edge detection algorithm as part of the edges in the carrier image. Besides, the algorithm is parameterized by three parameters: The size of the Gaussian filter, a low threshold value, and a high threshold value. These parameters can yield to different outputs for the same input image and secret data. As a result, discovering the inner-workings of the algorithm would be considerably ambiguous, misguiding steganalysts from the exact location of the covert data. Experiments showed a simulation tool codenamed GhostBit, meant to cover and uncover secret data using the proposed algorithm. As future work, examining how other image processing techniques such as brightness and contrast adjustment can be taken advantage of in steganography with the purpose ofgiving the communicating parties more preferences tomanipulate their secret communication.