High capacity information hiding scheme using VAD algorithm

Lin, Rong-San

doi:10.1109/icce-tw.2016.7521040

Cited by 2 publications

(8 citation statements)

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“…Then, the stateless coefficients were used to calculate residual energy, which was then compared with the threshold, so the VAD results kept invariable after steganography. Due to the silence compression function being optional for G.723.1 codec and there being some bits in the VoIP packet header to direct whether to use the silence compression function during encoding process, Lin [29] used the one free bit generated by disabling the silence compression function to mark the inactive frames embedded with secret messages. When decoding the VoIP streams at the receiver end, there is no need to run the VAD algorithm again and the secret messages are extracted from the inactive frames that have been marked.…”

Section: Related Workmentioning

confidence: 99%

“…Huang et al [28] and Lin [29] selected the parameters to embed secret messages by evaluating the effects after being modified. There are 101 bits per frame for steganography with 6.3 kbit/s mode, 81 bits per frame for steganography with 5.3 kbit/s mode, and the suitable parameters for steganography are listed in Tables 3 and 4.…”

Section: Steganography In Inactive Framementioning

confidence: 99%

“…Recently, Huang et al [28] improved the Voice Activity Detection (VAD) algorithm to keep the VAD result invariant after steganography and modified several types of parameter bits in inactive frames in G.723.1 with 6.3 kbit/s mode to embed the secret messages, whose steganographic bandwidth can reach up to 101 bits per frame. Lin [29] proposed another improved VAD algorithm to keep the VAD result unchanged after steganography and extended Huang's method to 5.3 kbit/s mode.As for VoIP steganalysis, there is no universal detection method currently, but some effective steganalysis methods [30][31][32][33][34][35][36][37] have been proposed to detect steganographic algorithms, which modify specific encoding parameters. For example, Li et al [30] pointed out that the codeword of LPC became asymmetrical after embedding secret messages and proposed a quantization codework correlation network model to detect LPC-based steganography, which has a good detection performance even in short sample length.…”

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Steganalysis of Inactive Voice-Over-IP Frames Based on Poker Test

et al. 2018

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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 test statistics of each type of encoding parameter bits as detection features, we present a steganalysis method based on a support vector machine. We evaluate the proposed method with a large quantity of speech samples encoded by G.723.1 and compare it with the entropy test. The experimental results show that the proposed method is effective, and largely outperforms the entropy test in any cases.

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Section: Related Workmentioning

confidence: 99%

Section: Steganography In Inactive Framementioning

confidence: 99%

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Steganalysis of Inactive Voice-Over-IP Frames Based on Poker Test

et al. 2018

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“…In general, VoIP-based steganography can be divided into two categories [6]- [9]. One employs the network protocols as carriers [10], [16]- [18], while the other hides information by modifying payloads in speech streams [7]- [9], [19]- [28]. Due to its high steganographic capacity, the second category has been the mainstream of VoIP-based steganography.…”

Section: Introductionmentioning

confidence: 99%

Detecting Steganography in Inactive Voice-Over-IP Frames Based on Statistic Characteristics of Fundamental Frequency

Tian¹,

Liu²,

Chang

et al. 2020

IEEE Access

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Steganography in inactive Voice-over-IP frames is a new technique of information hiding, which can achieve large steganographic capacity while maintaining excellent imperceptibility. To prevent the illegitimate use of this technique, the entropy-based and poker test-based steganalysis methods have been presented. However, the detection performance of these two methods is not so good for the cases of having small quantity of inactive frames or low embedding rates. Thus, we present a new steganalysis method based on statistic characteristics of fundamental frequency. Specifically, we employ the statistics for zero-crossing count (ZCC), including the average ZCC of inactive frames, the ratio between the average ZCC of inactive frames and that of all frames, and the difference between the average ZCC of inactive frames and their calibrated versions, to characterize the frame-level dynamic characteristic of speech signals; we utilize the average values of Mel-frequency cepstral coefficients (MFCCs) to represent the invariant characteristic of inactive frames; further, using the feature set consisting of the zero-crossing statistics and average MFCCs, we propose a support-vector-machine based steganalysis for inactive speech frames. The proposed steganalysis method is evaluated with a large number of ITU-T G.723.1 encoded speech samples, and compared with the existing methods. The experimental results demonstrate that the proposed method significantly outperforms the previous ones on detection accuracy, false positive rate and false negative rate for any given embedding rates or using the same number of inactive frames. Particularly, the proposed method can provide accurate detecting results for the existing steganographic methods only using very small quantity of inactive frames, and thereby be employed to detecting potential inactive-frame steganography behaviors in real-time speech streams.

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High capacity information hiding scheme using VAD algorithm

Cited by 2 publications

References 4 publications

Steganalysis of Inactive Voice-Over-IP Frames Based on Poker Test

Steganalysis of Inactive Voice-Over-IP Frames Based on Poker Test

Detecting Steganography in Inactive Voice-Over-IP Frames Based on Statistic Characteristics of Fundamental Frequency

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