A Bayesian approach to attack characterisation using robust watermarks

HD Knowles, DA Winne, CN Canagarajah, DR Bull

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)

Abstract

In this paper we propose the use of a Bayesian framework to allow characterisation of image tampering from a library of attacks. We use the double watermarking strategy proposed in our previous work to derive sufficient information to drive the classifier. A non-parametric Bayesian classifier, trained on data derived from Monte Carlo simulations is used. In addition to classification, the effects of varying the input parameters are studied. The results obtained show that the non-parametric Bayesian classifier has a very low misclassification rate for this type of problem. Explanations as to the nature of the results, and some of the practical considerations, are given.
Translated title of the contributionA Bayesian approach to attack characterisation using robust watermarks
Original languageEnglish
Title of host publicationVisual Communications and Image Processing 2003, Lugano, Switzerland
PublisherSociety of Photo-Optical Instrumentation Engineers (SPIE)
Pages851 - 861
Number of pages11
Volume5150 II
DOIs
Publication statusPublished - 8 Jul 2003

Fingerprint

Dive into the research topics of 'A Bayesian approach to attack characterisation using robust watermarks'. Together they form a unique fingerprint.

Cite this