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dc.contributor.authorFarid, Hanyen_US
dc.date.accessioned2004-10-08T20:37:17Z
dc.date.available2004-10-08T20:37:17Z
dc.date.issued1999-12-01en_US
dc.identifier.otherAIM-1657en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6678
dc.description.abstractWith 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.en_US
dc.format.extent1106172 bytes
dc.format.extent819825 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesAIM-1657en_US
dc.titleDetecting Digital Forgeries Using Bispectral Analysisen_US


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