scholarly journals High Security and Capacity of Image Steganography for Hiding Human Speech Based on Spatial and Cepstral Domains

2020 ◽  
Vol 8 (1) ◽  
pp. 95
Author(s):  
Yazen A. Khaleel
Keyword(s):  
Speech Signal ◽  
Vocal Tract ◽  
Color Image ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Mel Frequency Cepstral Coefficients ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Original Speech

A new technique of hiding a speech signal clip inside a digital color image is proposed in this paper to improve steganography security and loading capacity. The suggested technique of image steganography is achieved using both spatial and cepstral domains, where the Mel-frequency cepstral coefficients (MFCCs) are adopted, as very efficient features of the speech signal. The presented technique in this paper contributes to improving the image steganography features through two approaches. First is to support the hiding capacity by the usage of the extracted MFCCs features and pitches extracted from the speech signal and embed them inside the cover color image rather than directly hiding the whole samples of the digitized speech signal. Second is to improve the data security by hiding the secret data (MFCCs features) anywhere in the host image rather than directly using the least significant bits substitution of the cover image. At the recovering side, the proposed approach recovers these hidden features and using them to reconstruct the speech waveform again by inverting the steps of MFCCs extraction to recover an approximated vocal tract response and combine it with recovered pitch based excitation signal. The results show a peak signal to noise ratio of 52.4 dB of the stego-image, which reflect a very good quality and a reduction ratio of embedded data to about (6%–25%). In addition, the results show a speech reconstruction degree of about 94.24% correlation with the original speech signal.

scholarly journals Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 18 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain ◽  
E. Suresh Babu
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
The State ◽  
Image Steganography ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
State Of Art

Abstract This article proposes bit flipping method to conceal secret data in the original image. Here a block consists of 2 pixels and thereby flipping one or two LSBs of the pixels to hide secret information in it. It exists in two variants. Variant-1 and Variant-2 both use 7th and 8th bit of a pixel to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the Variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, Peak Signal to Noise Ratio (PSNR), hiding capacity, and the Quality Index (Q.I) of the proposed techniques has been compared with the results of the existing bit flipping technique and some of the state of art article.

scholarly journals Image Steganography using Improved Lsb-Mapping Technique with Enhanced Recovery Speed

2019 ◽  
Vol 8 (4) ◽  
pp. 11473-11478
Keyword(s):  
Data Hiding ◽  
Enhanced Recovery ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Cover Image ◽  
Mapping Technique ◽  
Secret Data ◽  
Logical Function ◽  
Hiding Capacity ◽  
Carrier Image

In recent days, for sending secret messages, we require secure internet. Image steganography is considered as the eminent tool for data hiding which provides better security for the data transmitted over internet. In the proposed work, the payload data is embedded using improved LSB-mapping technique. In this approach, two bits from each pixel of carrier image are considered for mapping and addition. Two bits of payload data can be embedded in one cover image pixel hence enhanced the hiding capacity. A logical function on addition is applied on 1st and 2nd bits of cover image pixel, and a mapping table is constructed which gives solution for data hiding and extraction. Simple addition function on stego pixel is performed to extract payload data hence increases the recovery speed. Here the secret data is not directly embedded but instead mapped and added with a number using modulo-4 strategy. Hence the payload data hidden using proposed approach provide more security and it can resist against regular LSB decoding approaches. The proposed work is implemented and tested for several gray scale as well as color images and compared with respect to parameters like peak signal to noise ratio and MSE. The proposed technique gives better results when compared and histogram of cover and stego images are also compared.

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 A New Reversible Data Hiding Technique Combined with Interpolation and Pixel Value Differencing Method

2020 ◽  
pp. 53-58
Author(s):  
Jayeeta Majumder ◽  
Chittaranjan Pradhan
Keyword(s):  
High Capacity ◽  
Main Idea ◽  
Image Steganography ◽  
Second Phase ◽  
Secret Data ◽  
Stego Image ◽  
Hiding Capacity ◽  
Small Distortion ◽  
Pixel Value ◽  
Pixel Value Differencing

Steganography is the popular security method that provides complete security for communicating secret details. Image steganography is a very interesting field because of the imperceptible way of hiding data in images, since small distortion in the images cannot be identified by a human eye. This is the main idea to develop image steganography algorithms to improve visual quality. Pixel Value Differencing is able to provide a high quality stego image in spite of the high capacity of the concealed information. This paper proposes the first the interpolation techniques with the pixel block then applying then the Pixel Value Differencing method. Here in the first phase the original image is portioned into 2X2 block then applying the nearest neighbour interpolation technique after that in the second phase PVD is used to embed the secret data. Then the new pixel value of the neighbouring pixel also calculated. In this paper one variant are proposed by using single range table. We observed that for both the variant PSNR value and the hiding capacity are increased.

scholarly journals Notice of Retraction Digital Image Steganography Using Bit Flipping

2018 ◽  
Vol 7 (1) ◽  
pp. 1
Author(s):  
Aditya Kumar Sahu ◽  
Gandharba Swain
Keyword(s):  
Digital Image ◽  
Quality Index ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Expert Committee ◽  
Original Image ◽  
Signal To Noise ◽  
Secret Data ◽  
Hiding Capacity ◽  
Secret Information

<p><strong>Notice of Retraction</strong><br /><br />-----------------------------------------------------------------------<br />After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IAES's Publication Principles.<br /><br />We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.<br /><br />The presenting author of this paper has the option to appeal this decision by contacting [email protected].<br /><br />-----------------------------------------------------------------------</p><p>This article proposes bit flipping method to conceal secret data in the original image. Here a section consists of 2 pixels and there by flipping one or two LSBs of the pixels to hide secret information in it. It exists in 2 variants. The variant-1 and variant-2 both use 7<sup>th</sup> and 8<sup>th</sup> bit to conceal the secret data. Variant-1 hides 3 bits per a pair of pixels and the variant-2 hides 4 bits per a pair of pixels. Our proposed method notably raises the capacity as well as bits per pixel that can be hidden in the image compared to existing bit flipping method. The image steganographic parameters such as, peak signal to noise ratio (PSNR), hiding capacity, and the quality index of the proposed techniques has been compared with the existing bit flipping technique</p>

scholarly journals Authentic Data Transmission in Image with Different LSB Methods

2019 ◽  
Vol 8 (6) ◽  
pp. 4625-4628
Keyword(s):  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Third Party ◽  
Secret Message ◽  
Secret Key ◽  
Secret Data ◽  
Stego Image ◽  
Audio Data ◽  
Carrier Image ◽  
Authentic Data

A technique to hide undisclosed information from third party as well, the method of investigation to conceal secret data into the cover frame like text, audio, image and video without any change in substantial results to the carrier image is nothing but Steganography. The contemporary safe and taut steganography of image represents an exigent form of transformation of the inserted secrecy for the receiver with getting undetected [1-5]. In Image steganography, image is the carrier and any secret message (audio or text or image) can be transmitted. This algorithm of LSB can be executed in embedding territory where the secret audio data is inserted into the LSB of envelope image for creating the stego image. This paper gives the hiding of audio data as secret data in an image file using LSB with secret key and an improved inverted LSB image Steganography with improved mean square error and peak signal to noise ratio.

scholarly journals High Capacity Image Steganography using Pixel Value Differencing Method with Data Compression using Neural Network

2019 ◽  
Vol 8 (12) ◽  
pp. 1800-1804
Keyword(s):  
Neural Network ◽  
Data Compression ◽  
Data Hiding ◽  
Image Steganography ◽  
Data Embedding ◽  
Least Significant Bit ◽  
Secret Data ◽  
Stego Image ◽  
Compression Technique ◽  
Hiding Capacity

The Digital Market Is Rapidly Growing Day By Day. So, Data Hiding Is Going To Increase Its Importance. Information Can Be Hidden In Different Embedding Mediums, Known As Carriers By Using Steganography Techniques. The Carriers Are Different Multimedia Medium Such As Images, Audio Files, Video Files, And Text Files .There Are Several Techniques Present To Achieve Data Hiding Like Least Significant Bit Insertion Method And Transform Domain Technique. The Data Hidden Capacity Inside The Cover Image Totally Depends On The Properties Of The Image Like Number Of Noisy Pixels. Data Compression Provides To Hide Large Amount Of Secret Data To Increase The Capacity And The Image Steganography Based On Any Neural Network Provides That The Size And Quality Of The Stego-Image Remains Unaltered After Data Embedding. In This Paper We Propose A New Method Combined With Data Compression Along With Data Embedding Technique And After Embedding To Maintain The Quality The Communication Channel Use The Neural Network. The Compression Technique Increase The Data Hiding Capacity And The Use Of Neural Network Maintain The Flow Of Data Processing Signal

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 Chaos-based Color Image Steganography Method Using 3 D Cat Map

2021 ◽  
pp. 3220-3227
Author(s):  
Sarab M. Hameed ◽  
Zuhair Hussein Ali ◽  
Ghadah K. AL-Khafaji ◽  
Safa Ahmed
Keyword(s):  
Color Image ◽  
Signal To Noise Ratio ◽  
Secret Message ◽  
Least Significant Bit ◽  
Stego Image ◽  
Hiding Capacity ◽  
Comparison Results ◽  
Information Hiding Capacity ◽  
High Level ◽  
Color Image Steganography

     Steganography is a technique to hide a secret message within a different multimedia carrier so that the secret message cannot be identified. The goals of steganography techniques include improvements in imperceptibility, information hiding, capacity, security, and robustness. In spite of numerous secure methodologies that have been introduced, there are ongoing attempts to develop these techniques to make them more secure and robust. This paper introduces a color image steganographic method based on a secret map, namely 3-D cat. The proposed method aims to embed data using a secure structure of chaotic steganography, ensuring better security. Rather than using the complete image for data hiding, the selection of the image band and pixel coordination is adopted, using the 3D map that produces irregular outputs for embedding a secret message randomly in the least significant bit (LSB) of the cover image. This increases the complexity encountered by the attackers. The performance of the proposed method was evaluated and the results reveal that the proposed method provides a high level of security through defeating various attacks, such as statistical attacks, with no detectable distortion in the stego-image. Comparison results ensure that the proposed method surpasses other existing steganographic methods regarding the Mean Square Error (MSE) and Peak Signal-to-Noise Ratio(PSNR).

scholarly journals Image steganography using least significant bit and secret map techniques

2020 ◽  
Vol 10 (1) ◽  
pp. 935
Author(s):  
Ashwaq Alabaichi ◽  
Maisa'a Abid Ali K. Al-Dabbas ◽  
Adnan Salih
Keyword(s):  
Quality Index ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Least Significant Bit ◽  
Secret Data ◽  
Hiding Capacity ◽  
Image Histogram ◽  
Image Fidelity ◽  
The Media ◽  
Key Sensitivity

In steganography, secret data are invisible in cover media, such as text, audio, video and image. Hence, attackers have no knowledge of the original message contained in the media or which algorithm is used to embed or extract such message. Image steganography is a branch of steganography in which secret data are hidden in host images. In this study, image steganography using least significant bit and secret map techniques is performed by applying 3D chaotic maps, namely, 3D Chebyshev and 3D logistic maps, to obtain high security. This technique is based on the concept of performing random insertion and selecting a pixel from a host image. The proposed algorithm is comprehensively evaluated on the basis of different criteria, such as correlation coefficient, information entropy, homogeneity, contrast, image, histogram, key sensitivity, hiding capacity, quality index, mean square error (MSE), peak signal-to-noise ratio (PSNR) and image fidelity. Results show that the proposed algorithm satisfies all the aforementioned criteria and is superior to other previous methods. Hence, it is efficient in hiding secret data and preserving the good visual quality of stego images. The proposed algorithm is resistant to different attacks, such as differential and statistical attacks, and yields good results in terms of key sensitivity, hiding capacity, quality index, MSE, PSNR and image fidelity.

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