The use of images and audio data for covert channels and image forgery has seen an explosion of interest during the past 15 years. This class focuses on the topic of analyzing digital image data for detection of covert communication and for detection of image alteration for deceptive purposes.

Steganography concentrates on hiding a message in an innocuous carrier to conceal the existence of the message. Its primary goal is undetectable message passing. Cryptography, on the other hand, is the study of scrambling a message so that if and when it is intercepted, it cannot be understood. Analyzing data in which payload has been hidden is called steganalysis, and a wide variety of analysis techniques are available to detect, extract, change or ultimately destroy the hidden information.  Results of steganalysis can also be used to change or improve existing embedding techniques.

Changing the scene content of an image to create a different but related picture is called digital forgery. Digital image forensics is a field that focuses on a variety of techniques including image acquisition properties and image processing to analyze image data to detect forgery. This course offers an introduction to steganography, steganalysis, and image forensics. Fundamental concepts in mathematical and statistical concepts are given that allows the student to understand and implement embedding and analysis techniques for steganography and image forgery detection.

“Hide nothing, for time, which sees all and hears all, exposes all.” Sophocles