Table of contents
- Matrix embedding
- Cost functions
- Machine/Deep Learning attacks
- Statistical attacks
- Tools & libraries
Syndrome Trellis Codes: A Python implementation of the steganography embedding technique presented in the paper “Minimizing embedding impact in steganography using trellis-coded quantization” by Tomáš Filler, Jan Judas and Jessica Fridrich.
PySTC: Python interface to Syndrome Trellis Codes (C++), presented in the paper “Minimizing Additive Distortion in Steganography using Syndrome-Trellis Codes” by Tomáš Filler, Jan Judas and Jessica Fridrich.
J-UNIWARD: A Python implementation of the steganography method for hidden information into JPEG images, proposed in the paper “Universal Distortion Function for Steganography in an Arbitrary Domain” by Vojtěch Holub, Jessica Fridrich and Tomáš Denemark.
HILL: A Python implementation of the steganography method for hiding information into bitmap images, proposed in the paper “A New Cost Function for Spatial Image Steganography” by Bin Li, Ming Wang, Jiwu Huang and Xiaolong Li.
Machine/Deep Learning attacks
ATS: Implementation of the ATS attack, presented in the paper “Unsupervised steganalysis based on artificial training sets” by Daniel Lerch-Hostalot and David Megías.
MA: Implementation of the manifold alignment technique, presented in the paper “Manifold alignment approach to cover source mismatch in steganalysis” by Daniel Lerch-Hostalot and David Megías.
PPD: Implementation of the PPD feature extractor, presented in the paper “LSB matching steganalysis based on patterns of pixel differences and random embedding” by Daniel Lerch-Hostalot and David Megías.
pyEC: Python Interface to the Matlab version of Ensemble Classifiers for Steganalysis, presented in the paper “Ensemble Classifiers for Steganalysis of Digital Media” by Jan Kodovský, Jessica Fridrich and Vojtěch Holub.
- Calibration Attack: Implementation of the attack to F5 algorithm (JPEG steganography) proposed in the paper Steganalysis of JPEG Images: Breaking the F5 Algorithm by Jessica Fridrich, Miroslav Goljan and Dorin Hogea.
- Watermarking examples: Implementation of some watermarking schemes proposed in the book Digital Watermarking and Steganography by I. J. Cox, M. L. Miller, J. A. Bloom, J. Fridrich and T. Kalker.
- System 1: E_BLIND/L_LC
Blind Embedding (E_BLIND) and Linear Correlation Detection (D_LC).
- System 2: E_FIXED_LC/L_LC
Fixed Linear Correlation Embedder (E_FIXED_LC) amd Linear Correlation Detection (D_LC).
- System 3: E_BLK_BLIND/D_BLK_CC
Block-Based, Blind Embedding (E_BLK_BLIND) and Correlation Coefficient Detection (D_BLK_CC)
- System 4: E_SIMPLE_8
8-Bit Blind Embedder (E_SIMPLE_8) and 8-Bit Detector (D_SIMPLE_8).
- System 5: E_TRELLIS_8/D_TRELLIS_8
Trellis-Coding Embedder (E_TRELLIS_8) and Viterbi Detector (D_TRELLIS_8).
- System 1: E_BLIND/L_LC
Tools & libraries
Python JPEG Toolbox: Toolbox for accessing low level JPEG information (DCT coefficients, quantization tables, …) with Python. Its interface is similar to the well-known Matlab JPEG Toolbox.
Aletheia: Aletheia is an open source image steganalysis tool for the detection of hidden messages in images. To achieve its objectives, Aletheia uses state-of-the-art machine learning techniques. It is capable of detecting different steganographic methods as for example LSB replacement, LSB matching and some kind of adaptive schemes.
Stego Retweet: A tool for hiding messages in Twitter using retweets. Using a list of hashtags provided by the user, this tool finds and retweets some tweets containing especial words. This allows to hide a message that can be read by the user who has the password. The capacity is of two characters per retweet.