Steganography integration into a low-bit rate speech codec

Low bit-rate speech codecs have been widely used in audio communications like VoIP and mobile communications, so that steganography in low bit-rate audio streams would have broad applications in practice. In this paper, the authors propose a new algorithm for steganography in low bit-rate VoIP audio streams by integrating information hiding into the process of speech encoding. The proposed algorithm performs data embedding while pitch period prediction is conducted during low bit-rate speech encoding, thus maintaining synchronization between information hiding and speech encoding. The steganography algorithm can achieve high quality of speech and prevent detection of steganalysis, but also has great compatibility with a standard low bit-rate speech codec without causing further delay by data embedding and extraction. Testing shows, with the proposed algorithm, the data embedding rate of the secret message can attain 4 bits / frame (133.3 bits / second)

Covert Voice over Internet Protocol communications based on spatial model

This paper presents a new spatial steganography model for covert communications over Voice over Internet Protocol (VoIP), providing a solution to the issue of increasing the capacity of covert VoIP channels without compromising the imperceptibility of the channels. Drawing from Orthogonal Modulation Theory in communications, the model introduced two concepts, orthogonal data hiding features and data hiding vectors, to covert VoIP communications. By taking into account the variation characteristics of VoIP audio streams in the time domain, a hiding vector negotiation mechanism was suggested to achieve dynamic self-adaptive ste-ganography in media streams. Experimental results on VoIP steganography show that the pro-posed steganographic method effectively depicted the spatial and temporal characteristics of VoIP audio streams, and enhanced robustness against detection of steganalysis tools, thereby improving the security of covert VoIP communications

Steganography in inactive frames of VoIP streams encoded by source codec

This paper describes a novel high capacity steganography algorithm for embedding data in the inactive frames of low bit rate audio streams encoded by G.723.1 source codec, which is used extensively in Voice over Internet Protocol (VoIP). This study reveals that, contrary to existing thoughts, the inactive frames of VoIP streams are more suitable for data embedding than the active frames of the streams, that is, steganography in the inactive audio frames attains a larger data embedding capacity than that in the active audio frames under the same imperceptibility. By analysing the concealment of steganography in the inactive frames of low bit rate audio streams encoded by G.723.1 codec with 6.3kbps, the authors propose a new algorithm for steganography in different speech parameters of the inactive frames. Performance evaluation shows embedding data in various speech parameters led to different levels of concealment. An improved voice activity detection algorithm is suggested for detecting inactive audio frames taking into packet loss account. Experimental results show our proposed steganography algorithm not only achieved perfect imperceptibility but also gained a high data embedding rate up to 101 bits/frame, indicating that the data embedding capacity of the proposed algorithm is very much larger than those of previously suggested algorithms

Fast Fourier Transform-based steganalysis of covert communications over streaming media

Steganalysis seeks to detect the presence of secret data embedded in cover objects, and there is an imminent demand to detect hidden messages in streaming media. This paper shows how a new steganalysis algorithm based on Fast Fourier Transform (FFT) can be used to detect the existence of secret data embedded in streaming media. The proposed algorithm uses machine parameter characteristics and a network sniffer to determine whether the Internet traffic contains streaming channels. The detected streaming data is then transferred from the time domain to the frequency domain through FFT. The distributions of power spectra in the frequency domain between original VoIP streams and stego VoIP streams are compared in turn using t-test, achieving the p-value of 7.5686E-176 which is below the threshold. Results indicate that the proposed FFT-based steganalysis algorithm is effective in detecting the secret data embedded in VoIP streaming media

Secure covert communications over streaming media using dynamic steganography

Streaming technologies such as VoIP are widely embedded into commercial and industrial applications, so it is imperative to address data security issues before the problems get really serious. This thesis describes a theoretical and experimental investigation of secure covert communications over streaming media using dynamic steganography. A covert VoIP communications system was developed in C++ to enable the implementation of the work being carried out. A new information theoretical model of secure covert communications over streaming media was constructed to depict the security scenarios in streaming media-based steganographic systems with passive attacks. The model involves a stochastic process that models an information source for covert VoIP communications and the theory of hypothesis testing that analyses the adversary‘s detection performance. The potential of hardware-based true random key generation and chaotic interval selection for innovative applications in covert VoIP communications was explored. Using the read time stamp counter of CPU as an entropy source was designed to generate true random numbers as secret keys for streaming media steganography. A novel interval selection algorithm was devised to choose randomly data embedding locations in VoIP streams using random sequences generated from achaotic process. A dynamic key updating and transmission based steganographic algorithm that includes a one-way cryptographical accumulator integrated into dynamic key exchange for covert VoIP communications, was devised to provide secure key exchange for covert communications over streaming media. The discrete logarithm problem in mathematics and steganalysis using t-test revealed the algorithm has the advantage of being the most solid method of key distribution over a public channel. The effectiveness of the new steganographic algorithm for covert communications over streaming media was examined by means of security analysis, steganalysis using non parameter Mann-Whitney-Wilcoxon statistical testing, and performance and robustness measurements. The algorithm achieved the average data embedding rate of 800 bps, comparable to other related algorithms. The results indicated that the algorithm has no or little impact on real-time VoIP communications in terms of speech quality (< 5% change in PESQ with hidden data), signal distortion (6% change in SNR after steganography) and imperceptibility, and it is more secure and effective in addressing the security problems than other related algorithms

Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates

Steganalysis with low embedding rates is still a challenge in the field of information hiding. Speech signals are typically processed by wavelet packet decomposition, which is capable of depicting the details of signals with high accuracy. A steganography detection algorithm based on the Markov bidirectional transition matrix (MBTM) of the wavelet packet coefficient (WPC) of the second-order derivative-based speech signal is proposed. On basis of the MBTM feature, which can better express the correlation of WPC, a Support Vector Machine (SVM) classifier is trained by a large number of Least Significant Bit (LSB) hidden data with embedding rates of 1%, 3%, 5%, 8%,10%, 30%, 50%, and 80%. LSB matching steganalysis of speech signals with low embedding rates is achieved. The experimental results show that the proposed method has obvious superiorities in steganalysis with low embedding rates compared with the classic method using histogram moment features in the frequency domain (HMIFD) of the second-order derivative-based WPC and the second-order derivative-based Mel-frequency cepstral coefficients (MFCC). Especially when the embedding rate is only 3%, the accuracy rate improves by 17.8%, reaching 68.5%, in comparison with the method using HMIFD features of the second derivative WPC. The detection accuracy improves as the embedding rate increases