NDLI: Digital audio forensics: a first practical evaluation on microphone and environment classification

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Digital audio forensics: a first practical evaluation on microphone and environment classification

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Digital audio forensics: a first practical evaluation on microphone and environment classification

Content Provider	ACM Digital Library
Author	Kraetzer, Christian Dittmann, Jana Oermann, Andrea Lang, Andreas
Abstract	In this paper a first approach for digital media forensics is presented to determine the used microphones and the environments of recorded digital audio samples by using known audio steganalysis features. Our first evaluation is based on a limited exemplary test set of 10 different audio reference signals recorded as mono audio data by four microphones in 10 different rooms with 44.1 kHz sampling rate and 16 bit quantisation. Note that, of course, a generalisation of the results cannot be achieved. Motivated by the syntactical and semantical analysis of information and in particular by known audio steganalysis approaches, a first set of specific features are selected for classification to evaluate, whether this first feature set can support correct classifications. The idea was mainly driven by the existing steganalysis features and the question of applicability within a first and limited test set. In the tests presented in this paper, an inter-device analysis with different device characteristics is performed while intra-device evaluations (identical microphone models of the same manufacturer) are not considered. For classification the data mining tool WEKA with K-means as a clustering and Naive Bayes as a classification technique are applied with the goal to evaluate their classification in regard to the classification accuracy on known audio steganalysis features. Our results show, that for our test set, the used classification techniques and selected steganalysis features, microphones can be better classified than environments. These first tests show promising results but of course are based on a limited test and training set as well a specific test set generation. Therefore additional and enhanced features with different test set generation strategies are necessary to generalise the findings.
Starting Page	63
Ending Page	74
Page Count	12
File Format	PDF
ISBN	9781595938572
DOI	10.1145/1288869.1288879
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-09-20
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Digital media forensics Multimedia authentication
Content Type	Text
Resource Type	Article

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