November 2019
Intermediate to advanced
346 pages
9h 36m
English
In this recipe, we will curate an LSB dataset and then train and test an ML model to detect the presence of LSB steganography in an image. Let's get started:
python aletheia.py lsbm-sim bossbase 0.40 bossbase_lsb
The result is a new folder named bossbase_lsb, which contains the BOSS images with embeddings. It does this using an LSB matching simulator.
./aletheia.py srm bossbase bossbase.fea
./aletheia.py srm bossbase_lsb bossbase_lsb.fea
The remaining steps can be run in a Python environment for your convenience.