Digital logic based encoding strategies for steganography on voice-over-IP

Tian, Hui; Zhou, Ke; Jiang, Hong; Feng, Dan

doi:10.1145/1631272.1631412

Cited by 5 publications

(3 citation statements)

References 18 publications

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“…According to , an IP header contains 64 bits where hidden data can be transmitted (and the same with an upper‐level protocols, like RTP), so choosing a place or a technique to hide one bit per frame is an arbitrary decision. One can relatively easily elaborate a technique that would change the location of such a signaling bit, which would lower the probability of detection, as was proposed in .…”

Section: Proposed Steganographic Methodsmentioning

confidence: 99%

Pitch‐based steganography for Speex voice codec

Janicki

2016

Security Comm Networks

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This paper presents an improved version of a steganographic algorithm for IP telephony called HideF0. It is based on approximating the F0 parameter, which is responsible for conveying information about the pitch of the speech signal. The bits saved due to simplification of the pitch contour are used for the hidden transmission. In our experiments, the proposed method was applied to the narrowband Speex codec working in five different modes, with bitrates between 5,950 bps and 24,600 bps. We showed that HideF0 was able to create hidden channels with steganographic bandwidths of around 200 bps at the expense of a steganographic cost of between 0.5 and 0.7 MOS, depending on the Speex mode. Because of placing the approximation flag in the voice packet header, the improved version of the proposed algorithm yielded a significantly lower decrease in speech quality, when compared with the original version of HideF0. In addition, for low bitrates of the hidden channel (i.e., below ca. 50 bps) it was able to operate without introducing any steganographic cost. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Proposed Steganographic Methodsmentioning

confidence: 99%

Pitch‐based steganography for Speex voice codec

Janicki

2016

Security Comm Networks

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“…Steganography and steganalysis can be seen as the two sides of the same coin. Steganography is a technique to hide sensitive data into di erent types of carries [18,22,25,42], while steganalysis is a countermeasure to steganography, focusing on detecting the hidden data in a given carrier. Text steganography is a branch of steganography that conceals messages in a cover text (generally takes a sentence as the minimum unit) without rising suspicions [31,39].…”

Section: Introductionmentioning

confidence: 99%

Few-shot Text Steganalysis Based on Attentional Meta-learner

Wen

Zhang

et al. 2022

Proceedings of the 2022 ACM Workshop on Information Hiding and Multimedia Security

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Text steganalysis is a technique to distinguish between steganographic text and normal text via statistical features. Current stateof-the-art text steganalysis models have two limitations. First, they need su cient amounts of labeled data for training. Second, they lack the generalization ability on di erent detection tasks. In this paper, we propose a meta-learning framework for text steganalysis in the few-shot scenario to ensure model fast-adaptation between tasks. A general feature extractor based on BERT is applied to extract universal features among tasks, and a meta-learner based on attentional Bi-LSTM is employed to learn task-speci c representations. A classi er trained on the support set calculates the prediction loss on the query set with a few samples to update the meta-learner. Extensive experiments show that our model can adapt fast among di erent steganalysis tasks through extremely few-shot samples, signi cantly improving detection performance compared with the state-of-the-art steganalysis models and other meta-learning methods. CCS CONCEPTS• Security and privacy → Human and societal aspects of security and privacy; • Computing methodologies → Natural language processing.

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“…With the advancement of computer communication networks, steganography has also penetrated into Internet based protocols and payloads [15], which brings both opportunities and challenges to communication security. In both of these two types of hiding applications, least significant steganography (LSB) related algorithms are always most popular and effective [10]. When it comes to low bit rate speech which is widely used as the payload in real time communications such as voice over Internet protocol (VoIP), restricted bandwidth and severe latency requirement are the most limiting factors for steganography [12].…”

Section: Introductionmentioning

confidence: 99%

State-based steganography in low bit rate speech

Zhou

Liu

Tian

et al. 2012

Proceedings of the 20th ACM International Conference on Multimedia

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Common least significant bit (LSB) relevant steganography methods in speech frames often base on bits evaluation by certain speech quality evaluation criterion and together with some coding and embedding strategies to enhance imperceptibility and efficiency. However, some embedding capabilities and security strategy are neglected. This paper proposes a state-based steganography method which fully investigates speech frame features in order to expand embedding capabilities and enhance steganography security. In the proposed method, embedding capabilities are measured by available numbers of states relative to current frame parameters rather than information bits. And secret information embedding procedure is performed by the chosen states mapped operations. This is a basic fine-grained steganography solution which is useful for other algorithms based on it. The experimental results have demonstrated that statebased method outperforms traditional LSB substitution in overall performance and introduces limited latency, which meets the realtime requirement in covert communications.

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Digital logic based encoding strategies for steganography on voice-over-IP

Cited by 5 publications

References 18 publications

Pitch‐based steganography for Speex voice codec

Pitch‐based steganography for Speex voice codec

Few-shot Text Steganalysis Based on Attentional Meta-learner

State-based steganography in low bit rate speech

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