Towards optimal design of data hiding algorithms against nonparametric adversary models

Alvaro A. Cárdenas, George V. Moustakides, John S. Baras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper presents a novel zero-sum watermarking game between a detection algorithm and a data hiding adversary. Contrary to previous research, the detection algorithm and the adversary we consider are both nonparametric in a continuous signal space, and thus they have no externally imposed limitations on their allowed strategies except for some distortion constraints. We show that in this framework no deterministic detection algorithm is optimal. We then find optimal randomized detection algorithms for different distortion levels and introduce a new performance tradeoff between completeness and accuracy when a detection algorithm does not have enough evidence to make an accurate decision.

Original languageEnglish (US)
Title of host publicationForty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings
Pages911-916
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
Event41st Annual Conference on Information Sciences and Systems, CISS 2007 - Baltimore, MD, United States
Duration: Mar 14 2007Mar 16 2007

Publication series

NameForty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings

Other

Other41st Annual Conference on Information Sciences and Systems, CISS 2007
CountryUnited States
CityBaltimore, MD
Period3/14/073/16/07

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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