scholarly journals High Capacity Image Steganography using Secret Key for Medical Information

2016 ◽  
Vol 9 (3) ◽  
Author(s):  
T. Somassoundaram ◽  
N. P. Subramaniam
Keyword(s):  
Medical Information ◽  
High Capacity ◽  
Image Steganography ◽  
Secret Key

scholarly journals Full Capacity Image Steganography Using Seven-Segment Display Pattern as Secret Key

2018 ◽  
Vol 14 (6) ◽  
pp. 753-763 ◽  
Author(s):  
Mohammed A. Fadhil Al-Husainy ◽  
Hamza Abbass A. Al-Sewadi
Keyword(s):  
Image Steganography ◽  
Secret Key ◽  
Full Capacity

scholarly journals A Secret-Key Image Steganography Technique using Random Chain Codes

2019 ◽  
Vol 10 (4) ◽  
pp. 731 ◽  
Author(s):  
Mohammed Abbas Fadhil Al-Husainy ◽  
Diaa Mohammed Uliyan
Keyword(s):  
Image Steganography ◽  
Secret Key ◽  
Chain Codes

scholarly journals Knight Tour for Image Steganography Technique

2019 ◽  
Vol 9 (1) ◽  
pp. 1610-1613
Keyword(s):  
Growth Rate ◽  
Data Hiding ◽  
Information Hiding ◽  
High Capacity ◽  
Image Steganography ◽  
Cover Image ◽  
The Internet ◽  
Sensitive Information ◽  
Image File ◽  
Ascii Code

The growth rate of the Internet is exceeding that of any previous technology. As the Internet has become the major medium for transferring sensitive information, the security of the transferred message has now become the utmost priority. To ensure the security of the transmitted data, Image steganography has emerged out as an eminent tool of information hiding. The frequency of availability of image file is high and provides high capacity. In this paper, a method of secure data hiding in image is proposed that uses knight tour positions and further 8-queen positions in 8*8 pixel blocks.The cover image is divided into 8*8 pixel blocks and pixels are selected from each block corresponding to the positions of Knight in 8*8 chessboard starting from different pixel positions. 8-pixel values are selected from alternate knight position. Selected pixels values converted to 8-bit ASCII code and result in 8* 8 bit matrix. 8-Queen’s solution on 8*8 chessboard is applied on 8*8 bit matrix. The bits selected from 8-Queens positions and compared with 8-bit ASCII code of message characters. The proposed algorithm changes the LSB of only some of the pixels based on the above comparison. Based on parameters like PSNR and MSE the efficiency of the method is checked after implementation. Then the comparison done with some already proposed techniques. This is how, image steganography showed interesting and promising results when compared with other techniques.

Bernoulli's Chaotic Map-Based 2D ECG Image Steganography

2019 ◽  
pp. 208-241 ◽  
Author(s):  
Anukul Pandey ◽  
Barjinder Singh Saini ◽  
Butta Singh ◽  
Neetu Sood
Keyword(s):  
Signal Processing ◽  
Chaotic Map ◽  
Image Steganography ◽  
Cover Image ◽  
Ecg Signal ◽  
Mean Square ◽  
Secret Key ◽  
Mean Square Difference ◽  
Electrocardiogram Ecg ◽  
Ecg Steganography

Signal processing technology comprehends fundamental theory and implementations for processing data. The processed data is stored in different formats. The mechanism of electrocardiogram (ECG) steganography hides the secret information in the spatial or transformed domain. Patient information is embedded into the ECG signal without sacrificing the significant ECG signal quality. The chapter contributes to ECG steganography by investigating the Bernoulli's chaotic map for 2D ECG image steganography. The methodology adopted is 1) convert ECG signal into the 2D cover image, 2) the cover image is loaded to steganography encoder, and 3) secret key is shared with the steganography decoder. The proposed ECG steganography technique stores 1.5KB data inside ECG signal of 60 seconds at 360 samples/s, with percentage root mean square difference of less than 1%. This advanced 2D ECG steganography finds applications in real-world use which includes telemedicine or telecardiology.

A Methodological Evaluation of Crypto-Watermarking System for Medical Images

2016 ◽  
pp. 189-217
Author(s):  
Anna Babu ◽  
Sonal Ayyappan
Keyword(s):  
Medical Information ◽  
Medical Images ◽  
Secret Key ◽  
Encrypted Data ◽  
Number Of Patients ◽  
Detailed Assessment ◽  
Content Recovery ◽  
Secure Transmission ◽  
Methodological Evaluation

Health care institution demands exchange of medical images of number of patients to sought opinions from different experts. In order to reduce storage and for secure transmission of the medical images, Crypto-Watermarking techniques are adopted. The system is considered to be combinations of encryption technique with watermarking or steganography means adopted for safe transfer of medical images along with embedding of optional medical information. The Digital Watermarking is the process of embedding data to multimedia content. This can be done in spatial as well as frequency domain of the cover image to be transmitted. The robustness against attacks is ensured while embedding the encrypted data into transform domain, the encrypted data can be any secret key for the content recovery or patient record or the image itself. This chapter presents basic aspects of crypto-watermarking technique, as an application. It gives a detailed assessment on different approaches of crypto-watermarking for secure transmission of medical images and elaborates a case study on it.

scholarly journals A NEW AND ADAPTIVE SECURITY MODEL FOR PUBLIC COMMUNICATION BASED ON CORRELATION OF DATA FRAMES

2019 ◽  
Vol 59 (2) ◽  
pp. 126-133
Author(s):  
Haider Tarish Haider ◽  
Dhiaa Halboot Muhsen ◽  
Haider Ismael Shahadib ◽  
Ong Hang See
Keyword(s):  
Information Technologies ◽  
High Capacity ◽  
Data Communication ◽  
Superior Performance ◽  
Secret Message ◽  
Communication Model ◽  
Security Model ◽  
Secret Key ◽  
Proposed Model ◽  
Capacity Data

Recent developments in communication and information technologies, plus the emerging of the Internet of Things (IoT) and machine to machine (M2M) principles, create the need to protect data from multiple types of attacks. In this paper, a secure and high capacity data communication model is proposed to protect the transmitted data based on identical frames between a secret and cover data. In this model, the cover data does not convey any embedded data (as in normal steganography system) or modify the secret message (as in traditional cryptography techniques). Alternatively, the proposed model sends the positions of the cover frames that are identical with the secret frames to the receiver side in order to recover the secret message. One of the significant advantages of the proposed model is the size of the secret key message which is considerably larger than the cover size, it may be even hundred times larger. Accordingly, the experimental results demonstrate a superior performance in terms of the capacity rate as compared to the traditional steganography techniques. Moreover, it has an advantage in terms of the required bandwidth to send the data or the required memory for saving when compared to the steganography methods, which need a bandwidth or memory up to 3-5 times of the original secret message. Where the length of the secret key (positions of the identical frames) that should be sent to the receiver increases by only 25% from the original secret message. This model is suitable for applications with a high level of security, high capacity rate and less bandwidth of communication or low storage devices.

Pixel Prediction-Based Image Steganography by Support Vector Neural Network

2020 ◽  
Author(s):  
Reshma V K ◽  
Vinod Kumar R S
Keyword(s):  
Neural Network ◽  
Medical Image ◽  
Medical Information ◽  
Similarity Index ◽  
Image Steganography ◽  
Secret Message ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Prediction Scheme

Abstract Securing the privacy of the medical information through the image steganography process has gained more research interest nowadays to protect the privacy of the patient. In the existing works, least significant bit (LSB) replacement strategy was most popularly used to hide the sensitive contents. Here, every pixel was replaced for achieving higher privacy, but it increased the complexity. This work introduces a novel pixel prediction scheme-based image steganography to overcome the complexity issues prevailing in the existing works. In the proposed pixel prediction scheme, the support vector neural network (SVNN) classifier is utilized for the construction of a prediction map, which identifies the suitable pixels for the embedding process. Then, in the embedding phase, wavelet coefficients are extracted from the medical image based on discrete wavelet transform (DWT) and embedding strength, and the secret message is embedded into the HL wavelet band. Finally, the secret message is extracted from the medical image on applying the DWT. The experimentation of the proposed pixel prediction scheme is done by utilizing the medical images from the BRATS database. The proposed pixel prediction scheme has achieved high performance with the values of 48.558 dB, 0.50009 and 0.9879 for the peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation factor, respectively.

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