A pattern classification framework for theoretical analysis of component forensics

TitleA pattern classification framework for theoretical analysis of component forensics
Publication TypeConference Papers
Year of Publication2008
AuthorsSwaminathan A, M. Wu, Liu KJR
Conference NameAcoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Date Published2008/04/31/4
Keywordsanalysis;information, classification;, classification;parameter, component, estimation;pattern, forensics;component, forensics;pattern, identification;forensic, parameter, processing;nonintrusive

Component forensics is an emerging methodology for forensic analysis that aims at estimating the algorithms and parameters in each component of a digital device. This paper proposes a theoretical foundation to examine the performance limits of component forensics. Using ideas from pattern classification theory, we define formal notions of identifiability of components in the information processing chain. We show that the parameters of certain device components can be accurately identified only in controlled settings through semi non-intrusive forensics, while the parameters of some others can be computed directly from the available sample data via complete non-intrusive analysis. We then extend the proposed theoretical framework to quantify and improve the accuracies and confidence in component parameter identification for several forensic applications.