Speech authentication system using digital watermarking and pattern recovery
Pattern Recognition Letters
Internet image archaeology: automatically tracing the manipulation history of photographs on the web
MM '08 Proceedings of the 16th ACM international conference on Multimedia
A Survey of Passive Image Tampering Detection
IWDW '09 Proceedings of the 8th International Workshop on Digital Watermarking
A bibliography on blind methods for identifying image forgery
Image Communication
Digital image forensics: a booklet for beginners
Multimedia Tools and Applications
MiFor '11 Proceedings of the 3rd international ACM workshop on Multimedia in forensics and intelligence
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
Homomorphic signatures for digital photographs
FC'11 Proceedings of the 15th international conference on Financial Cryptography and Data Security
Exposing MP3 audio forgeries using frame offsets
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special Issue on Multimedia Security
Detection of doctored images using correlations of PSF
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
An image splicing detection based on interpolation analysis
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Exposing digital audio forgeries in time domain by using singularity analysis with wavelets
Proceedings of the first ACM workshop on Information hiding and multimedia security
Image splicing verification based on pixel-based alignment method
IWDW'12 Proceedings of the 11th international conference on Digital Forensics and Watermaking
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With the rapid increase in low-cost and sophisticated digital technology the need for techniques to authenticate digital material will become more urgent. In this paper we address the problem of authenticating digital signals assuming no explicit prior knowledge of the original. The basic approach that we take is to assume that in the frequency domain a ``natural'''' signal has weak higher-order statistical correlations. We then show that ``un-natural'''' correlations are introduced if this signal is passed through a non-linearity (which would almost surely occur in the creation of a forgery). Techniques from polyspectral analysis are then used to detect the presence of these correlations. We review the basics of polyspectral analysis, show how and why these tools can be used in detecting forgeries and show their effectiveness in analyzing human speech.