A non-subsampled Shearlet transform based approach for heartbeat sound watermarking

In order to satisfy the requirements of retrieval time-efficiency and security for encrypted speech data retrieval in the cloud environment, and to improve the impact of noise on the robustness and discrimination for the speech perceptual hashing scheme, an encrypted speech retrieval algorithm based on Chirp-Z transform and perceptual hashing second feature extraction is proposed in this paper. The speech owner first processes the original speech file by pre-processing, framing, and adding window. The features of the original speech file is extracted by Chirp-Z transform combined with the sparse random matrix to construct a hash sequence. Then encrypt the original speech file based on the m sequence and upload it to the cloud to ensure the security of information. By processing the speech perceptual hashing feature, the speech features are re-extracted, and the speech is evenly classified by k-means clustering technique. The binary string of several hundred bits is converted into a decimal number. Finally, the second feature is stored in system hash index table of the cloud. When the user retrieves, the query speech is denoised and the hash sequence is extracted. Then the secondary features of the hash sequence are extracted and matched with the encrypted speech features in the cloud system hash index table to obtain the retrieval result. The experimental results show that the proposed algorithm greatly compresses the information capacity of speech features, significantly improves the retrieval time-efficiency, with strong robustness and discrimination, and has a good retrieval effect on noisy speech.

An encrypted speech retrieval algorithm based on Chirp-Z transform and perceptual hashing second feature extraction

In this paper, a robust and blind speech watermarking technique is proposed using a combined scheme based on discrete cosine transform (DCT) and discrete wavelet transform (DWT) Algorithms within signal sub-sampling. To achieve good imperceptibility, hybridization is implemented against many attacks such as: re-quantization, cropping, echo, amplification and additive white Gaussian noise (AWGN). We profit from the advantages of correlation between two successive samples so that we used signal sub-sampling. Obtained results, compared successfully to recent researches, show the robustness of our proposed approach.

Blind speech watermarking using hybrid scheme based on DWT/DCT and sub-sampling

In this paper we give a kind of generalized Fibonacci sequence in which necessary and sufficient conditions is also given in convergence.The generalized Fibonacci sequence can prove that square roots of integer is either integer or irrational.

A Generalized Fibonacci Sequence and Its Use

Watermarking has attained wide consideration for copyright security of multimedia information. Audio watermarking scheme using discrete wavelet transform and singular value decomposition (SVD) along with encryption is proposed in this article. Transform domain coefficients undergo SVD and then utilizing Fibonacci numbers encrypted watermark data is inserted into the singular values to ensure achievable acquirement of watermark. Proposed algorithm utilizes chaotic and AES encrypted watermarks for embedding to accelerate the scale of security. High imperceptible attribute, robust nature and high payload are achieved using the proposed strategy. Experimental results show that the audio watermarking scheme is not only inaudible, but also robust against various common signal processing attacks such as noise addition, filtering,equantization, echo, invert and compression.

Compressed domain secure, robust and high-capacity audio watermarking

In recent times audio watermark has become the centre of attention due to rapid growth of data transmission rates on internet, which has often allowed the unauthorized usage of digital audio files. This paper proposes a Discrete Wavelet Transform (DWT) based blind audio watermarking system. The initial audio undergoes wavelet based approach and later we divide it into frames. Here Fibonacci numbers is used to embed the watermark. SNR values along with error rate are the parameters calculated for execution of this technique. This method provides robust character to various data processing operations like echo, smoothness and reverberation. Greater contents with high imperceptibility is attained by the mechanism as can be interpreted by the simulation outcomes.

http://ieeexplore.ieee.org/iel7/7839736/7857433/07857479.pdf

Audio watermarking in wavelet domain using Fibonacci numbers

Innovative developments in computer technology has made distribution of data easier. But it has also put forth a new challenge to secure these multimedia data from privacy. In any kind of information system, data security and confidentiality services are generally required. In this paper we present a new secure audio watermarking technique based on Fast Fourier Transform (FFT) along with encryption. It combines Advanced Encryption Standard (AES) algorithm and a blind audio watermarking technique based on FFT along with Fibonacci numbers. Combining the encryption and watermarking algorithm enhances the security of watermark. The performance of this scheme is calculated using signal to noise ratio and bit error rate. Results indicate that the method is not only secure but also robust against various signal processing attacks with high imperceptibility.

A secure audio watermarking employing AES technique

Watermarking methods have been utilized for safeguarding contents against unlawful replication. New immune watermark introduction and retrieval mechanism constituting FFT based approach along with chaotic encryption is presented here. Encrypting the procedure develops a secure environment for the scheme. The primary audio undergoes Fast Fourier Transformation. Introduction of encrypted secret contents is accomplished adopting Fibonacci numbers. Retrieval of mark is achieved by non-informed scheme. Error rate as well as SNR outcomes are the execution specifications computed for this method. Here robust quality in opposition to distinct processing actions like reverberation, echo and smoothness is administered. Also greater imperceptibility procured by this method demonstrates the proprietary rights of initial content.

Uma R. Nair

Papers

Compressed domain secure, robust and high-capacity audio watermarking

Audio watermarking in wavelet domain using Fibonacci numbers

A secure audio watermarking employing AES technique

Encrypted Audio Watermarking in Frequency Domain