2018
DOI: 10.3390/sym10080336
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Steganalysis of Inactive Voice-Over-IP Frames Based on Poker Test

Abstract: This paper concentrates on the detection of steganography in inactive frames of low bit rate audio streams in Voice over Internet Protocol (VoIP) scenarios. Both theoretical and experimental analyses demonstrate that the distribution of 0 and 1 in encoding parameter bits becomes symmetric after a steganographic process. Moreover, this symmetry affects the frequency of each subsequence of parameter bits, and accordingly changes the poker test statistical features of encoding parameter bits. Employing the poker … Show more

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Cited by 2 publications
(5 citation statements)
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“…Steganalysis [33][34][35] is very popular for detecting hidden messages in individual digitized objects. In addition to the very fact of transmission, it is able (in some cases) to determine the message itself, the methods used, to decrypt it, etc.…”
Section: Features Of Digital Steganographymentioning
confidence: 99%
“…Steganalysis [33][34][35] is very popular for detecting hidden messages in individual digitized objects. In addition to the very fact of transmission, it is able (in some cases) to determine the message itself, the methods used, to decrypt it, etc.…”
Section: Features Of Digital Steganographymentioning
confidence: 99%
“…In this section, we evaluate the performance of the proposed method, and compare it with the entropy-based and poker test-based methods [35]. In the steganalysis experiments, all the SVM-based classifiers are implemented based on LibSVM [53] with RBF kernel, where the default parameter setting is adopted.…”
Section: Performance Evaluation a Experimental Setupmentioning
confidence: 99%
“…As for the steganalysis of VoIP, there have been also many fruitful studies [13]- [15], [29]- [35]. For example, Lin et al [15] introduced a recurrent neural network to detect quantization index modulation-based steganography for LPC parameters in G.729a speech streams, which can achieve excellent detection performance, even for very short speech samples, and significantly outperforms the steganalysis based on quantization codeword correlation network [29].…”
Section: Introductionmentioning
confidence: 99%
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