Artistic Curve Steganography Carried by Musical Audio

TL;DR

This paper introduces a novel steganography method that embeds artistic 2D and 3D curves into musical audio by encoding geometric properties into different frequency components, ensuring robustness against compression and imperceptibility to listeners.

Contribution

The work presents a new geometric-based audio steganography scheme that faithfully preserves and hides artistic curves in music using a simple, efficient encoding and decoding process.

Findings

The scheme effectively preserves curve geometry after lossy compression.

Hidden curves are undetectable to human listeners in listening tests.

The method successfully encodes complex 3D shapes and images into audio.

Abstract

In this work, we create artistic closed loop curves that trace out images and 3D shapes, which we then hide in musical audio as a form of steganography. We use traveling salesperson art to create artistic plane loops to trace out image contours, and we use Hamiltonian cycles on triangle meshes to create artistic space loops that fill out 3D surfaces. Our embedding scheme is designed to faithfully preserve the geometry of these loops after lossy compression, while keeping their presence undetectable to the audio listener. To accomplish this, we hide each dimension of the curve in a different frequency, and we perturb a sliding window sum of the magnitude of that frequency to best match the target curve at that dimension, while hiding scale information in that frequency's phase. In the process, we exploit geometric properties of the curves to help to more effectively hide and recover them. Our scheme is simple and encoding happens efficiently with a nonnegative least squares framework, while decoding is trivial. We validate our technique quantitatively on large datasets of images and audio, and we show results of a crowd sourced listening test that validate that the hidden information is indeed unobtrusive.