A Real-time Implementation for the Speech Steganography using Short-Time Fourier Transformior Secured Mobile Communication

Steganography can be described as approach of masking an undisclosed message with a normal message which is known as the Carrier message signal. DSP techniques, such as LSB encoding, have historically been implemented for secret information hiding. Utilization ofsteganography functions of deep neural networks for voice data is something this paper will present. This paper also demonstrate that the steganography techniques suggested for vision are less suitable for speech signals this paper present a implementation technique that involves the use of ISTFT and STFT as differentiablelayers in the network. Empirically, the efficacy of the proposed methods based on multiple datasets of speech should be demonstrated and the outcome are examined quantitatively and qualitatively. Using of multiple decoders or a single conditional decoder helps to hide multiple signals in a single carrier signal. Finally, under various channel distortion situations, this model Qualitative studies indicate that human listeners cannot detect changes made to the carrier and hence the decoded messages are highly intelligible.

Optimized Multirate Wideband Speech Steganography for Improving Embedding Capacity Compared with Neighbor-Index-Division Codebook Division Algorithm

Aim: The main motive of this study is to perform Adaptive Multi Rate Wideband (AMR-WB) Speech Steganography in network security to produce the stego speech with less loss of quality while increasing embedding capacities. Materials and Methods: TIMIT Acoustic-Phonetic Continuous Speech Corpus dataset consists of about 16000 speech samples out of which 1000 samples are taken and 80% pretest power for analyzing the speech steganography. AMR-WB Speech steganography is performed by Diameter Neighbor codebook partition algorithm (Group 1) and Neighbor Index Division codebook division algorithm (Group 2). Results: The AMR-WB speech steganography using DN codebook partition obtained average quality rate of 2.8893 and NID codebook division algorithm obtained average quality rate of 2.4196 in the range of 300bps embedding capacity. Conclusion: The outcomes of this study proves that the decrease in quality in NID is twice more than the DN based steganography while increasing the embedding capacities.

Hybrid Speech Steganography System using SS-RDWT with IPDP-MLE approach

In the last two decades, it has been observed that there have been remarkable advancements in digital media communication. It has lots of advantages and business potential as it needs no physical media or transport. However, digital media can also create several big problems for media owners due to unauthorized use, ease of replication, plasticity, and equivalence of works in digital form. The possible solution is to secure digital media by cover writing which can also referred as steganography. Therefore, this article focusing on development of hybrid speech steganography system using spread spectrum-based redundant discrete wavelet transform (SS- RDWT). In general, speech steganography utilizes cover speech to embed the secrete message, however, the cover speech might be larger in size and contains many pauses, which requires more storage capacity, higher computational time, and even higher power usage results in system performance degradation. Hence, in addition to the proposed SS-RDWT approach, an intelligent pause detection protocol (IPDP) with maximum likelihood estimation (MLE) technique is employed for removing pause from cover speech signal, which reduces the transmission bandwidth, storage capacity and power consumption as well. Simulation results demonstrate that proposed hybrid steganography using integrated SS-RDWT with IPDP-MLE approach obtained superior performance as compared to state-of-art approaches.