A new scheme for covert communication via 3G encoded speech

Miao, Haibo; Huang, Liusheng; Chen, Zhili; Yang, Wei; Hawbani, Ammar

doi:10.1016/j.compeleceng.2012.05.003

Cited by 46 publications

(53 citation statements)

References 22 publications

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“…The existing methods for AMR audio steganography [4] [5] are based on this idea, they embed secret messages in the last pulse position of each track implemented by restricting the search space for pulse positions, in such a way that pulse combination of the codevector matches a Geiser proposed a steganographic FCB restriction rule for AMR-NB 12.2kbit/s mode in [4]. At each AMR subframe, there are 40 pulse positions located in five tracks according to Table I.…”

Section: B Amr Steganographymentioning

confidence: 99%

“…Working on the principle of Algebraic Code Excited Linear Prediction (ACELP), the fixed codebook (FCB) structure of AMR is based on interleaved single-pulse permutation (ISPP) design and adopts the non-exhaustive depth-first tree search, which means the FCB parameters in AMR speech codec have some redundancy, so it is feasible to embed secret information by choosing another alternative suboptimal code vector and would not degrade synthetic speech quality. The existing methods for AMR audio steganography [4] [5] are based on this idea. Geiser [4] proposes a steganography of hiding digital data in ACELP speech codec utilizing the alternative search strategy for FCB.…”

mentioning

confidence: 99%

“…This method has a high embedding capacity and it allows embedding 2kbit/s of hidden data into AMR bitstream with a negligible effect on the subjective quality of the coded speech. For AMR-WB (AMR for Wide Band) codec, Miao and Huang [5] presents an adaptive suboptimal pulse combination constrained method to embed data. They adjust the last pulse position to keep some mapping relationship between other non-zero pulse positions in the same track and secret information to encode secret messages during the process of FCB search, which is similar to [4].…”

mentioning

confidence: 99%

“…In this paper, we propose an AMR steganalysis algorithm based on the probability of same pulse position (SPP) in the same track, which can achieve effective detection for both of the two existing AMR steganography methods [4] [5].…”

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confidence: 99%

See 3 more Smart Citations

AMR Steganalysis Based on the Probability of Same Pulse Position

Ren

Cai

Tang

et al. 2015

IEEE Trans.Inform.Forensic Secur.

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This paper presents a method for detection of Adaptive Multi-Rate (AMR) audio steganography. AMR audio codec is an audio data compression scheme optimized for speech coding, and widely used in some mobile telecommunications system. The AMR audio steganography schemes are emerging recently and they embed secret messages by modifying the non-zero pulse positions which are determined by fixed codebook (FCB) search in AMR compression procedure. Those methods have high embedding capacity and good imperceptivity. We have observed that those steganography schemes will cause the probability of same pulse positions in the same track increasing. Based on this phenomenon, this paper presents a set of steganalysis features of the probability of same pulse position (SPP). The support vector machine (SVM) is applied to the proposed features and used as the steganalyzer. The performance of the scheme is tested on a database containing approximately 140,714 audios. Experimental results show that the correct detection rate of our proposed method is above 90% when the embedding bit rate is 30% or above, and can reach above 85% for cover audios.

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Section: B Amr Steganographymentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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AMR Steganalysis Based on the Probability of Same Pulse Position

Ren

Cai

Tang

et al. 2015

IEEE Trans.Inform.Forensic Secur.

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show abstract

“…It can achieve high quality of stegospeech and prevent statistical steganalysis, but the embedding rate is still low (only about 133.3 bps). And an adaptive suboptimal pulse combination constrained (ASOPCC) method was presented in [14] to embed data into compressed speech signal of AMR-WB codec. However, most of the PESQ scores in different coding modes are not high.…”

Section: Introductionmentioning

confidence: 99%

A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

Chen

Xiao

et al. 2018

Security and Communication Networks

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Steganography is a means of covert communication without revealing the occurrence and the real purpose of communication. The adaptive multirate wideband (AMR-WB) is a widely adapted format in mobile handsets and is also the recommended speech codec for VoLTE. In this paper, a novel AMR-WB speech steganography is proposed based on diameter-neighbor codebook partition algorithm. Different embedding capacity may be achieved by adjusting the iterative parameters during codebook division. The experimental results prove that the presented AMR-WB steganography may provide higher and flexible embedding capacity without inducing perceptible distortion compared with the state-of-the-art methods. With 48 iterations of cluster merging, twice the embedding capacity of complementary-neighbor-vertices-based embedding method may be obtained with a decrease of only around 2% in speech quality and much the same undetectability. Moreover, both the quality of stego speech and the security regarding statistical steganalysis are better than the recent speech steganography based on neighbor-index-division codebook partition.

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Towards blind detection of steganography in low‐bit‐rate speech streams

Sun

Tian

Mazurczyk

et al. 2022

Int J of Intelligent Sys

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To prevent the abuse of low‐rate speech‐based steganography from threatening cyberspace security, the corresponding steganalysis approaches have been developed and received significant attention from research community. However, most existing steganalysis methods assume that steganography methods are known in advance, which in practice is impractical. That is why, in this paper, we present three blind detection schemes suitable for steganography in low‐bit‐rate speech streams. The first is based on mixed sample data augmentation. It randomly selects a certain proportion of steganographic samples from the sample set of each steganographic method to form a training set together with the original carrier samples for training to enhance the robustness of the model. The second relies on decision fusion where first step is to train a dedicated classification model for each steganography method and then use a majority voting mechanism in the detection stage to fuse the outputs of each model to give the final detection result. Compared to the other two steganalysis schemes, the third one design the detection model based on self‐paced ensemble according to the distribution characteristics of speech samples. Its main idea is to fully train multiple base classifiers through multiple iterations as well as under‐sampling processes, and organically fuse them to form a powerful ensemble classifier. In each iteration, differing from the traditional ensemble classifier solution, we put more attention to the steganographic samples at the decision boundary for the under‐sampling process of the steganography set composed of multiple steganography methods, rather than randomly selecting steganographic samples. The steganographic samples at the decision boundary are searched using the classification hardness given by the ensemble classifier trained in the last iteration, which is more informative and more conducive to improve the performance of base classifiers. The experimental results show that the proposed three schemes can achieve efficient blind detection for low‐bit‐rate speech‐based steganography, and the steganalysis scheme based on the self‐paced ensemble has the best performance. Specifically, when the embedding rate is at 30%, the accuracy of the steganalysis scheme based on self‐paced ensemble is more than 85%, while the accuracy of the other two steganalysis method is less than 80%. Additionally, the steganalysis scheme based on the self‐paced ensemble learning even outperforms dedicated detectors for specific steganographic methods in terms of recall for steganographic sample detection.

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A new scheme for covert communication via 3G encoded speech

Cited by 46 publications

References 22 publications

AMR Steganalysis Based on the Probability of Same Pulse Position

AMR Steganalysis Based on the Probability of Same Pulse Position

A Novel AMR-WB Speech Steganography Based on Diameter-Neighbor Codebook Partition

Towards blind detection of steganography in low‐bit‐rate speech streams

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