LFU:online

After completing the course, students are familiar with basic methods of digital steganography and steganalysis, i.e., hiding secret messages into inconspicuous objects and detecting their presence, respectively. To do so, students use selected digital image processing methods as well as binary classifiers, especially learning-based detectors.

The lectures will cover the following topics:

- Security notions for digital media
- Digital image forensics
- Image processing
- Image compression
- Steganography by least-significant bit (LSB) replacement and LSB matching
- Analytical attacks against LSBR
- Steganography in JPEG images
- Coding for information hiding
- Adaptive steganography, criteria of adaptiveness
- Feature-based classification for steganalysis
- Steganalysis using deep learning

In the second half of the semester, students will be assigned a small programming project implementing concepts from research in steganography or steganalysis.
At the end, students will present their solution in the class.

The lecture conveys theoretical knowledge, which is then used in oral and written tasks.
The exercises involve programming tasks as well as conceptual work and on-paper calculation.
The project aimed at reproducing of existing research further deepends the understanding.
The lecture and the literature are in English.

Continuous assessment based on participation, exercise sheets, written tests, and a submitted project.

Fridrich: Steganography in Digital Media
Katzenbeisser, Petitcolas: Information Hiding. Ch 2.-3.

Prior knowledge in signal processing and cryptography is recommended.

Allocation of places in courses with a limited number of participants (PS, SE, VU, PJ)

In courses with a limited number of participants, course places are allocated as follows:

1. Students for whom the study duration would be extended due to the postponement are to be given priority.

2. If the criteria in no. 1 do not suffice, first, students for whom this course is part of a compulsory module are to be given priority, and second, students for whom this course is part of an elective module.

3. If the criteria in no. 1 and 2 do not suffice, the available places are drawn by random.

Curriculum MA Computer Science 2021W