Biblio

ECG signals are often corrupted by 50 Hz noise, the frequency from the power supply. So it becomes quite necessary to remove Power Line Interference (PLI) from the ECG signal. The reference ECG signal data was taken from the MIT-BIH database. Different filtering techniques comprising of Discrete Wavelet Transform (DWT), Normalized Least Mean Square (NLMS) filter, Finite Impulse Response (FIR) filter and Infinite Impulse Response (IIR) filter were used in this paper for denoising the ECG signal which was corrupted by the PLI. Later, the comparison was made among the methods, to find the best methodology to denoise the corrupted ECG signal. The parameters that were used for the comparison are Mean Square Error (MSE), Mean Absolute Error (MAE), Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR). Higher values of SNR & PSNR and lower values of MSE & MAE define the best denoising algorithm.

Now-a-days, video steganography has developed for a secured communication among various users. The two important factor of steganography method are embedding potency and embedding payload. Here, a Multiple Object Tracking (MOT) algorithmic programs used to detect motion object, also shows foreground mask. Discrete wavelet Transform (DWT) and Discrete Cosine Transform (DCT) are used for message embedding and extraction stage. In existing system Least significant bit method was proposed. This technique of hiding data may lose some data after some file transformation. The suggested Multiple object tracking algorithm increases embedding and extraction speed, also protects secret message against various attackers.

A multipurpose color image watermarking method is presented to provide \textcopyright protection and ownership verification of the multimedia information. For robust color image watermarking, color watermark is utilized to bring universality and immense applicability to the proposed scheme. The cover information is first converted to Red, Green and Blue components image. Each component is transformed in wavelet domain using DWT (Discrete Wavelet Transform) and then decomposition techniques like Singular Value Decomposition (SVD), QR and Schur decomposition are applied. Multiple watermark embedding provides the watermarking scheme free from error (false positive). The watermark is modified by scrambling it using Arnold transform. In the proposed watermarking scheme, robustness and quality is tested with metrics like Peak Signal to Noise Ratio (PSNR) and Normalized Correlation Coefficient (NCC). Further, the proposed scheme is compared with related watermarking schemes.

In this paper, an innovative approach to keyboard user monitoring (authentication), using keyboard dynamics and founded on the concept of time series analysis, is presented. The work is motivated by the need for robust authentication mechanisms in the context of on-line assessment such as those featured in many online learning platforms. Four analysis mechanisms are considered: analysis of keystroke time series in their raw form (without any translation), analysis consequent to translating the time series into a more compact form using either the Discrete Fourier Transform or the Discrete Wavelet Transform, and a "benchmark" feature vector representation of the form typically used in previous related work. All four mechanisms are fully described and evaluated. A best authentication accuracy of 99% was obtained using the wavelet transform.

Audio Steganography is the technique of hiding any secret information behind a cover audio file without impairing its quality. Data hiding in audio signals has various applications such as secret communications and concealing data that may influence the security and safety of governments and personnel and has possible important applications in 5G communication systems. This paper proposes an efficient secure steganography scheme based on the high correlation between successive audio signals. This is similar to the case of differential pulse coding modulation technique (DPCM) where encoding uses the redundancy in sample values to encode the signals with lower bit rate. Discrete Wavelet Transform (DWT) of audio samples is used to store hidden data in the least important coefficients of Haar transform. We use the benefit of the small differences between successive samples generated from encoding of the cover audio signal wavelet coefficients to hide image data without making a remarkable change in the cover audio signal. instead of changing of actual audio samples so this doesn't perceptually degrade the audio signal and provides higher hiding capacity with lower distortion. To further increase the security of the image hiding process, the image to be hidden is divided into blocks and the bits of each block are XORed with a different random sequence of logistic maps using hopping technique. The performance of the proposed algorithm has been estimated extensively against attacks and experimental results show that the proposed method achieves good robustness and imperceptibility.

As increasingly more enterprises are deploying cloud file-sharing services, this adds a new channel for potential insider threats to company data and IPs. In this paper, we introduce a two-stage machine learning system to detect anomalies. In the first stage, we project the access logs of cloud file-sharing services onto relationship graphs and use three complementary graph-based unsupervised learning methods: OddBall, PageRank and Local Outlier Factor (LOF) to generate outlier indicators. In the second stage, we ensemble the outlier indicators and introduce the discrete wavelet transform (DWT) method, and propose a procedure to use wavelet coefficients with the Haar wavelet function to identify outliers for insider threat. The proposed system has been deployed in a real business environment, and demonstrated effectiveness by selected case studies.

Image Denoising nowadays is a great Challenge in the field of image processing. Since Discrete wavelet transform (DWT) is one of the powerful and perspective approaches in the area of image de noising. But fixing an optimal threshold is the key factor to determine the performance of denoising algorithm using (DWT). The optimal threshold can be estimated from the image statistics for getting better performance of denoising in terms of clarity or quality of the images. In this paper we analyzed various methods of denoising from the sonar image by using various thresholding methods (Vishnu Shrink, Bayes Shrink and Neigh Shrink) experimentally and compare the result in terms of various image quality parameters. (PSNR,MSE,SSIM and Entropy). The results of the proposed method show that there is an improvenment in the visual quality of sonar images by suppressing the speckle noise and retaining edge details.

In this paper, we investigate the performance of multiple-input multiple-output aided coded interleave division multiple access (IDMA) system for secured medical image transmission through wireless communication. We realize the MIMO profile using four transmit antennas at the base station and three receive antennas at the mobile station. We achieve bandwidth efficiency using discrete wavelet transform (DWT). Further we implement Arnold's Cat Map (ACM) encryption algorithm for secured medical transmission. We consider celulas as medical image which is used to differentiate between normal cell and carcinogenic cell. In order to accommodate more users' image, we consider IDMA as accessing scheme. At the mobile station (MS), we employ non-linear minimum mean square error (MMSE) detection algorithm to alleviate the effects of unwanted multiple users image information and multi-stream interference (MSI) in the context of downlink transmission. In particular, we investigate the effects of three types of delay-spread distributions pertaining to Stanford university interim (SUI) channel models for encrypted image transmission of MIMO-IDMA system. From our computer simulation, we reveal that DWT based coded MIMO- IDMA system with ACM provides superior picture quality in the context of DL communication while offering higher spectral efficiency and security.

In our digital world internet is a widespread channel for transmission of information. Information that is transmitted can be in form of messages, images, audios and videos. Due to this escalating use of digital data exchange cryptography and network security has now become very important in modern digital communication network. Cryptography is a method of storing and transmitting data in a particular form so that only those for whom it is intended can read and process it. The term cryptography is most often associated with scrambling plaintext into ciphertext. This process is called as encryption. Today in industrial processes images are very frequently used, so it has become essential for us to protect the confidential image data from unauthorized access. In this paper Advanced Encryption Standard (AES) which is a symmetric algorithm is used for encryption and decryption of image. Performance of Advanced Encryption Standard algorithm is further enhanced by adding a key stream generator W7. NIOS II soft core processor is used for implementation of encryption and decryption algorithm. A system is designed with the help of SOPC (System on programmable chip) builder tool which is available in QUARTUS II (Version 10.1) environment using NIOS II soft core processor. Developed single core system is implemented using Altera DE2 FPGA board (Cyclone II EP2C35F672). Using MATLAB the image is read and then by using DWT (Discrete Wavelet Transform) the image is compressed. The image obtained after compression is now given as input to proposed AES encryption algorithm. The output of encryption algorithm is given as input to decryption algorithm in order to get back the original image. The implementation of which is done on the developed single core platform using NIOS II processor. Finally the output is analyzed in MATLAB by plotting histogram of original and encrypted image.

This paper reports a research work on how to transmit a secured image data using Discrete Wavelet Transform (DWT) in combination of Advanced Encryption Standard (AES) with low power and high speed. This can have better quality secured image with reduced latency and improved throughput. A combined model of DWT and AES technique help in achieving higher compression ratio and simultaneously it provides high security while transmitting an image over the channels. The lifting scheme algorithm is realized using a single and serialized DT processor to compute up to 3-levels of decomposition for improving speed and security. An ASIC circuit is designed using RTL-GDSII to simulate proposed technique using 65 nm CMOS Technology. The ASIC circuit is implemented on an average area of about 0.76 mm2 and the power consumption is estimated in the range of 10.7-19.7 mW at a frequency of 333 MHz which is faster compared to other similar research work reported.