A study on the use of perceptual hashing to detect manipulation of embedded messages in images
This addresses the need for secure detection of tampering in embedded image messages, but it is incremental as it builds on existing embedding and hashing techniques.
The study tackled the problem of distinguishing between unintended image compression and malicious manipulation of embedded messages using perceptual hashing, finding that integer wavelet transform embedding with Karhunen-Loeve-transform compression performed best, though not perfectly in all cases.
Typically, metadata of images are stored in a specific data segment of the image file. However, to securely detect changes, data can also be embedded within images. This follows the goal to invisibly and robustly embed as much information as possible to, ideally, even survive compression. This work searches for embedding principles which allow to distinguish between unintended changes by lossy image compression and malicious manipulation of the embedded message based on the change of its perceptual or robust hash. Different embedding and compression algorithms are compared. The study shows that embedding a message via integer wavelet transform and compression with Karhunen-Loeve-transform yields the best results. However, it was not possible to distinguish between manipulation and compression in all cases.