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

scholarly journals An Image Steganography Algorithm using Fractional Discrete Wavelet Transform with Advanced Encryption System

2020 ◽  
Vol 9 (5) ◽  
pp. 541-546
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Mean Square Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Signal To Noise ◽  
Noise Ratio

The research constitutes a distinctive technique of steganography of image. The procedure used for the study is Fractional Random Wavelet Transform (FRWT). The contrast between wavelet transform and the aforementioned FRWT is that it comprises of all the benefits and features of the wavelet transform but with additional highlights like randomness and partial fractional value put up into it. As a consequence of the fractional value and the randomness, the algorithm will give power and a rise in the surveillance layers for steganography. The stegano image will be acquired after administrating the algorithm which contains not only the coated image but also the concealed image. Despite the overlapping of two images, any diminution in the grade of the image is not perceived. Through this steganographic process, we endeavor for expansion in surveillance and magnitude as well. After running the algorithm, various variables like Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR) are deliberated. Through the intended algorithm, a rise in the power and imperceptibility is perceived and it can also support diverse modification such as scaling, translation and rotation with algorithms which previously prevailed. The irrefutable outcome demonstrated that the algorithm which is being suggested is indeed efficacious.

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 KOMPARASI METODE DWT DAN SVD UNTUK MENGUKUR KUALITAS CITRA STEGANOGRAFI

2020 ◽  
Vol 5 (2) ◽  
pp. 100
Author(s):  
Dedi Darwis ◽  
A. Ferico Octaviansyah Pasaribu
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Singular Value ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Stego Image ◽  
Value Decomposition

<em>Keamanan data saat ini merupakan hal yang sangat penting diera digital karena komunikasi harus bersifat rahasia dan aman. Salah satu cara untuk berkomunikasi secara digital adalah steganografi yaitu pengembangan dari kriptografi, teknik ini memiliki cara menyembunyikan data dan informasi pada media lainnya misalkan seperti citra digital karena media ini sering digunakan dalam pertukaran informasi dan data. Algoritma steganografi yang digunakan pada penelitian ini adalah Discrete Wavelet Transform (DWT) dan Singular Value Decomposition (SVD) kedua metode ini merupakan bagian dari steganografi yang sama-sama memanfaatkan domain transform pada pengolahan citra digital dan memiliki kecepatan yang tinggi dalam penyisipan pesan rahasia ke suatu gambar. Masalah yang selama ini terjadi pada steganografi adalah kualitas stego image yang dihasilkan pada steganografi mengalami perubahan pada kualitas citra, sehingga perbedaan antara cover image dan stego image akan sangat terlihat. Penerapan metode DWT dan SVD pada penelitian ini diimplementasikan dengan bahasa pemrograman Python 2. Berdasarkan hasil pengujian yang dilakukan metode DWT dapat menghasilkan kualitas citra pada stego image yang lebih baik jika dibandingkan metode SVD yaitu menghasilkan nilai MSE nilai rata-rata 0,0046 db. Hasil perhitungan nilai PSNR juga membuktikan bahwa metode DWT menghasilkan kualitas citra  lebih baik dari dari metode SVD yaitu menghasilkan nilai rata-rata 63,47 db.</em>

scholarly journals AN ENHANCED IMAGE STEGANOGRAPHY TECHNIQUE FOR HIGH-SECURITY COMMUNICATION

2021 ◽  
Vol 9 (2) ◽  
pp. 1-6
Author(s):  
Apoorv Mahajan ◽  
Arpan Singh Rajput
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Data Hiding ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Minimum Mean Squared Error ◽  
The Matrix ◽  
Value Decomposition

Purpose of the study: We propose an approach to hide data in an image with minimum Mean Squared Error (MSE) and maximum Signal-to-Noise ratio (SNR) using Discrete Wavelet Transform (DWT). Methodology: The methodology used by us considers the application of Discrete Wavelet transform to transform the values of the image into a different domain for embedding the information to be hidden in the image and then using Singular Value decomposition we decomposed the matrix values of the image for better data hiding. Main Findings: The application of the SVD function gave the model a better performance and also RED pixel values with the High-High frequency domain are a better cover for hiding data. Applications of this study: This article can be used for further research on applications of mathematical and frequency transformation functions on data hiding. It can also be used to implement a highly secure image steganography model. Novelty/Originality of this study: The application of Discrete Wavelet Transform has been used before but the application of SVD and hiding data in the H-H domain to obtain better results is original.

scholarly journals Design and Implementation of Lifting Based Wavelet and Adaptive LSB Steganography to Secret Data Sharing Through Image on FPGA

2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Kokila B. Padeppagol ◽  
Sandhya Rani M H
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Data ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Secret Data ◽  
Secret Image ◽  
Design And Implementation

Image steganography is an art of hiding images secretly within another image. There are several ways of performing image steganography; one among them is the spatial approach.The most popular spatial domain approach of image steganography is the Least Significant Bit (LSB) method, which hides the secret image pixel information in the LSB of the cover image pixel information. In this paper a LSB based steganography approach is used to design hardware architecture for the Image steganography. The Discrete Wavelet Transform (DWT) is used here to transform the cover image into higher and lower wavelet coefficients and use these coefficients in hiding the secret image. the design also includes encryption of secret image data, to provide a higher level of security to the secret image. The steganography system involving the stegno module and a decode module is designed here. The design was simulated, synthesized and implemented on Artix -7 FPGA. The operation hiding and retrieving images was successfully verified through simulations.

scholarly journals Stego-eHealth: An eHealth System for Secured Transfer of Medical Images using Image Steganography

2021 ◽  
Author(s):  
Nandhini Subramanian ◽  
, Jayakanth Kunhoth ◽  
Somaya Al-Maadeed ◽  
Ahmed Bouridane
Keyword(s):  
Medical Information ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Health Care Systems ◽  
Image Steganography ◽  
Cover Image ◽  
Stego Image ◽  
Hiding Capacity ◽  
Secret Image ◽  
Care Systems

COVID pandemic has necessitated the need for virtual and online health care systems to avoid contacts. The transfer of sensitive medical information including the chest and lung X-ray happens through untrusted channels making it prone to many possible attacks. This paper aims to secure the medical data of the patients using image steganography when transferring through untrusted channels. A deep learning method with three parts is proposed – preprocessing module, embedding network and the extraction network. Features from the cover image and the secret image are extracted by the preprocessing module. The merged features from the preprocessing module are used to output the stego image by the embedding network. The stego image is given as the input to the extraction network to extract the ingrained secret image. Mean Squared Error (MSE) and Peak Signal-to-Noise Ratio (PSNR) are the evaluation metrics used. Higher PSNR value proves the higher security; robustness of the method and the image results show the higher imperceptibility. The hiding capacity of the proposed method is 100% since the cover image and the secret image are of the same size.

scholarly journals An Image Steganography Method Hiding Secret Data into Coefficients of Integer Wavelet Transform Using Pixel Value Differencing Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Avinash K. Gulve ◽  
Madhuri S. Joshi
Keyword(s):  
Wavelet Transform ◽  
Frequency Domain ◽  
Spatial Domain ◽  
Image Steganography ◽  
Cover Image ◽  
Integer Wavelet Transform ◽  
Wavelet Coefficients ◽  
Secret Data ◽  
Secret Information ◽  
Integer Wavelet

The image steganography systems use either the spatial domain or the frequency domain to hide the secret information. The proposed technique uses spatial domain technique to hide secret information in the frequency domain. The cover image is transformed using integer wavelet transform to obtain four subbands: LL, LH, HL, and HH. Then, the PVD approach is used to hide the secret information in the wavelet coefficients of all the four subbands. For improving the security of the hidden information, the proposed method first modifies the difference between two wavelet coefficients of a pair and then uses the modified difference to hide the information. This makes extraction of secret data from the stego image difficult even if the steganography method fails. The result shows that the proposed technique outperforms other PVD based techniques in terms of security of secret information and hiding capacity of cover 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.

Sign in / Sign up

Export Citation Format

Share Document