Informatik, TU Wien

Digital Image Forensics and its Implications for Multivariate Data Analysis

The field of image forensics aims to restore trust in digital images, by providing means to analyze images and uncover forgery.

Abstract

Images are essential sources of information that are used to visually represent a multitude of data: digital documents, photographs, medical images, astronomic observations and even microscopy data. However, modern software editing tools undermine the trust in images and, in consequence, their potential as sources of information. The field of image forensics aims to restore trust in digital images, by providing means to analyze images and uncover forgery. Images are formed by complex physical processes, and its interaction with electronical and software components. These interactions imprint diverse features and patterns in the final image, and understanding these patterns is the work of a forensics analyst. It’s through finding either broken or unusual patterns in complex, multivariate data that image forgery is uncovered. This is also true for other types of malicious fraud detection; such as bank frauds, malware analysis or insurance fraud. While on a high level images and bank transactions seem to share little similarities, for a forensic analyst they can be seen as the same: massive amounts of data describing interaction between different elements. In this presentation, the fundamentals of the field of digital image forensics are introduced, and then related to bank fraud detection on a discussion about forensics analysis itself.

Note

This talk is organized by the Institute of Software Technology and Interactive Systems.