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Detecting Digital Forgeries Using Bispectral Analysis

Author(s)
Farid, Hany
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Abstract
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.
Date issued
1999-12-01
URI
http://hdl.handle.net/1721.1/6678
Other identifiers
AIM-1657
Series/Report no.
AIM-1657

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  • AI Memos (1959 - 2004)

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