An Improved ECG Steganography Using Integer Wavelet Transform and Offset Coefficient with LSB Substitution

2021 ◽  
Author(s):  
Ching-Yu Yang ◽  
Wen-Fong Wang
Keyword(s):  
Wavelet Transform ◽  
Personal Information ◽  
Signal To Noise Ratio ◽  
Computation Time ◽  
Integer Wavelet Transform ◽  
Wearable Electronics ◽  
Least Significant Bit ◽  
Hiding Capacity ◽  
Offset Coefficient ◽  
Integer Wavelet

Abstract In this work, we present an improved steganography for electrocardiogram (ECG) hosts to solve the issues of existing ECG steganographic methods, which have less hiding capacity and insufficient signal-to-noise ratio (SNR)/ peak SNR (PSNR). Based on the integer wavelet transform (IWT) domain, sensitive (or private) data such as patients’ data and personal information can be efficiently embedded in an ECG host via the IWT coefficient adjustment and the least significant bit (LSB) technique. Simulations confirmed that the SNR/ PSNR, and payload of the proposed method outperform those of existing techniques. In addition, the proposed method is capable of resisting attacks, such as cropping, Gaussian noise-addition inversion, scaling, translation, and truncation attacks from third parties (or adversaries). Due to the fast computation time, the proposed method can be employed in portable biometric devices or wearable electronics.

scholarly journals A Juxtaposition Between Integer Wavelet Transform and Discrete Wavelet Transform for Secure Image Steganography

2020 ◽  
Vol 9 (5) ◽  
pp. 1019-1023
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Integer Wavelet Transform ◽  
Stego Image ◽  
Hiding Capacity ◽  
Integer Wavelet

Image steganography is a technique that is used to hide information. The information can be of various types like image, video, or audio. Steganography is done so that no one apart from the correct receiver can retrieve the information. This paper consists of all advantages and highlights of the wavelet transform but with the additional features like randomness and some default values that are already built-in it. Various algorithms can be used in steganography and they provide good hiding capacity and low detectability. Here we have hidden the image into the cover image using Integer Wavelet Transform (IWT) and also using Discrete Wavelet Transform (DWT) and compared which technique gives better results. It is very difficult to predict the presence of a hidden image inside the stego image since it looks exactly like the cover image. There is no loss in quality from the secret image to the extracted image since the PSNR (Peak Signal to noise ratio) is high for both of them. This process was done using both DWT and IWT and the results prove that that the IWT technique is not only simpler but also more efficient than the DWT technique since it gives higher PSNR values. Through the proposed algorithm, an increase in the strength and imperceptibility is noticed and it can also maintain various transformations such as scaling, translation, and rotation with algorithms that already exist. The final results, after comparing both the transforms prove that the algorithm which is being proposed in IWT is indeed effective

A New Steganography Method Using Integer Wavelet Transform and Least Significant Bit Substitution

2019 ◽  
Vol 62 (11) ◽  
pp. 1639-1655
Author(s):  
Manashee Kalita ◽  
Themrichon Tuithung ◽  
Swanirbhar Majumder
Keyword(s):  
Wavelet Transform ◽  
Data Hiding ◽  
Integer Wavelet Transform ◽  
Embedding Capacity ◽  
Least Significant Bit ◽  
Stego Image ◽  
Significant Similarity ◽  
Chi Squared ◽  
Integer Wavelet

Abstract Steganography is a data hiding technique, which is used for securing data. Both spatial and transform domains are used to implement a steganography method. In this paper, a novel transform domain method is proposed to provide a better data hiding method. The method uses a multi-resolution transform function, integer wavelet transform (IWT) that decomposes an image into four subbands: low-low, low-high, high-low and high-high subband. The proposed method utilizes only the three subbands keeping the low-low subband untouched which helps to improve the quality of the stego image. The method applies a coefficient value differencing approach to determine the number of secret bits to be embedded in the coefficients. The method shows a good performance in terms of embedding capacity, imperceptibility and robustness. A number of metrics are computed to show the quality of the stego image. It can also withstand RS steganalysis, Chi-squared test and Subtractive Pixel Adjacency Matrix steganalysis successfully. The deformation of the histogram and Pixel Difference Histogram for different embedding percentages are also demonstrated, which show a significant similarity with the original cover image. The proposed method shows an achievement of 2.3bpp embedding capacity with a good quality of stego image.

scholarly journals Pengamanan Citra Dengan Kombinasi Modified Serpent IWT Dengan Modified Logistic Chaotic Map

2021 ◽  
Vol 8 (3) ◽  
pp. 1090-1104
Author(s):  
Kelvin Lysander ◽  
Allwin M Simarmata ◽  
Denniel Lusandy ◽  
Iswandi Iswandi
Keyword(s):  
Wavelet Transform ◽  
Chaotic Map ◽  
Cover Image ◽  
Integer Wavelet Transform ◽  
Logistic Chaotic Map ◽  
Integer Wavelet

Abstrak Algoritma kriptografi dapat digunakan untuk mengamankan citra. Salah satu algoritma kriptografi yang dapat digunakan untuk mengenkripsi citra adalah algoritma Serpent. Namun, algoritma Serpent memerlukan proses enkripsi dan dekripsi yang lama. Selain itu, pengenkripsian saja tidaklah cukup karena akan menimbulkan kecurigaan sehingga informasi akan rentan dicuri. Maka diperlukan teknik steganografi seperti metode Integer Wavelet Transform (IWT). Citra rahasia akan dienkripsi terlebih dahulu dengan menggunakan metode Modified Serpent, dimana modifikasi Serpernt mengubah proses transformasi substitusi byte (DES S-box) menjadi list bilangan prima 257 yang memiliki 128 generator untuk digunakan sebagai kunci di setiap putarannya. Pada proses penyisipan dengan metode IWT, perlu ditentukan posisi bit dan piksel pada cover image yang akan disisipkan sebuah pesan. Untuk menentukan posisi tersebut, maka digunakanlah fungsi chaos. Setelah itu, dapat dilakukan proses ekstraksi terhadap citra stego yang dihasilkan pada proses penyisipan untuk memperoleh kembali bit yang tersimpan didalamnya. Kumpulan bit tersebut dapat didekripsi sehingga akan diperoleh kembali citra rahasia semula.

scholarly journals Wavelet based Reversible Image Watermarking with Logistic Encryption for Health Informatics Systems

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3567-3570
Keyword(s):  
Wavelet Transform ◽  
Execution Time ◽  
Health Informatics ◽  
Binary Data ◽  
Image Watermarking ◽  
Reversible Watermarking ◽  
Integer Wavelet Transform ◽  
Integer Wavelet ◽  
Reversible Image Watermarking ◽  
Watermarking Scheme

Health Informatics systems preserves the patient’s digital records. Two techniques that help in this process are watermarking and encryption. In this paper a reversible image watermarking scheme with logistic encryption is presented. The reversible watermarking is utilizing the concept of integer wavelet transform. The image is divided into sub bands and then the binary data is hidden in these sub bands. The watermarked wavelet sub bands are passed through logistic encryption module which scrambles the coefficients. These coefficients are then sent to inverse wavelet transform for image reconstruction. This process helps encrypt the image though spectral scrambling, thus resulting in faster and better encryption. The proposed algorithm outperforms the exiting algorithms in terms of execution time and the level of encryption.

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