Welcome

Hello and welcome to my page. My name is Daniel Lerch and this is a personal site mainly dedicated to steganography, the ancient art and science of hidden communication.

“Two accomplices in a crime have been arrested and are about to be locked in widely separated cells. Their only means of communication after they are locked up will be by way of messages conveyed for them by trustees – who are known to be agents of the warden. (…). The prisoners, (…) are willing to accept these conditions (…) to be able to communicate at all, since they need to coordinate their plans. To do this they will have to deceive the warden by finding a way of communicating secretly (…)”

The Prisoners' Problem and the Subliminal Channel
Gustavus J. Simmons

Latest updates

• 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.
  [ Updated on 2021-06-13 ]

• Practical attack on LSB replacement: OpenStego and OpenPuff: Blog post about the detection of images embedded using LSB replacement (OpenStego and OpenPufF), using the Aletheia steganalysis tool.
  [ Updated on 2021-06-13 ]

• Introduction to steganalysis with Aletheia: Blog post about the basic usage of the Aletheia steganalysis tool.
  [ Updated on 2021-06-12 ]

• Identifying the steganography scheme: Blog post about the identification of the steganography scheme using the Aletheia steganalysis tool.
  [ Updated on 2021-06-12 ]

• Practical attack on F5: Blog post about the detection of JPEG images embedded with F5, using the Aletheia steganalysis tool.
  [ Updated on 2021-06-04 ]

• Practical attack on Steghide: Blog post about the detection of JPEG images embedded with Steghide, using the Aletheia steganalysis tool.
  [ Updated on 2021-06-03 ]

• 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.
  [ Updated on 2021-02-15 ]

• 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.
  [ Updated on 2020-10-08 ]

• 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.
  [ Updated on 2020-08-24 ]

• 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.
  [ Updated on 2020-08-10 ]

• 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.
  [ Updated on 2020-06-25 ]

• 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.
  [ Updated on 2020-03-23 ]

• 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.
  [ Updated on 2019-03-18 ]

• 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.
  [ Updated on 2018-03-27 ]

• ATS: Implementation of the ATS attack, presented in the paper “Unsupervised steganalysis based on artificial training sets” by Daniel Lerch-Hostalot and David Megías.
  [ Updated on 2017-05-10 ]

• 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.
  [ Updated on 2017-04-02 ]

• 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.
  [ Updated on 2017-04-02 ]

• 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.
  [ Updated on 2017-04-02 ]