SubjectsSubjects(version: 850)
Course, academic year 2019/2020
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Steganography and Digital Media - NMMB436
Title in English: Steganografie a digitální média
Guaranteed by: Department of Algebra (32-KA)
Faculty: Faculty of Mathematics and Physics
Actual: from 2019
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:2/0 Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
State of the course: not taught
Language: English, Czech
Teaching methods: full-time
Additional information: http://www.karlin.mff.cuni.cz/~kozlik/sdm/
Guarantor: RNDr. Andrew Kozlík, Ph.D.
Class: M Mgr. MMIB
M Mgr. MMIB > Povinně volitelné
Classification: Informatics > Computer Graphics and Geometry
Mathematics > Algebra
Incompatibility : NMIB029
Interchangeability : NMIB029
Annotation -
Last update: doc. Mgr. et Mgr. Jan Žemlička, Ph.D. (14.05.2019)
The course is concerned with the basic notions of steganography in the context of standard image file formats. The course may not be taught every academic year.
Course completion requirements - Czech
Last update: doc. Mgr. et Mgr. Jan Žemlička, Ph.D. (11.06.2019)

Předmět je zakončen ústní zkouškou.

Literature -
Last update: T_KA (14.05.2013)

Jessica Fridrich: Steganography in Digital Media: Principles, Algorithms, and Applications

Requirements to the exam - Czech
Last update: RNDr. Andrew Kozlík, Ph.D. (02.10.2018)

Zkouška je ústní. Student si vylosuje otázky a dostane čas na přípravu poznámek. Otázky korespondují se sylabem přednášky v rozsahu, ve kterém byla jednotlivá témata vyložena na přednášce.

Syllabus -
Last update: RNDr. Andrew Kozlík, Ph.D. (02.10.2018)

Digital image formats (raster, palette and JPEG format).

Digital image acquisition (Bayer filter, image processing, noise).

LSB embedding and ±1 embedding.

Histogram attack on LSB embedding.

Quantitative attack on Jsteg.

Sample pairs analysis.

Steganography in palette images, optimal-parity embedding.

Attack on embedding with optimal parity assignment.

Model-preserving steganography (OutGuess embedding algorithm).

F5 embedding algorithm.

Embedding while reducing color depth and its efficiency.

Matrix embedding and its efficiency.

Matrix embedding algorithm using a minimum-distance decoder.

Lower bound on the covering radius depending on relative payload.

Perfect codes and the upper bound on embedding efficiency.

Sum and difference covering sets.

Wet paper theorem, perturbed quantization, embedding with double JPEG compression, double-layered ±1 embedding.

Embedding using the Viterbi algorithm.

 
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