scholarly journals A Safe and Secured Medical Textual Information Using an Improved LSB Image Steganography

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Roseline Oluwaseun Ogundokun ◽  
Oluwakemi Christiana Abikoye
Keyword(s):  
Medical Information ◽  
Medical Data ◽  
Image Steganography ◽  
Medical Information System ◽  
Least Significant Bit ◽  
Stego Image ◽  
Performance Metric ◽  
Challenging Tasks ◽  
Multimedia Technologies ◽  
Lsb Technique

Safe conveyance of medical data across unsecured networks nowadays is an essential issue in telemedicine. With the exponential growth of multimedia technologies and connected networks, modern healthcare is a huge step ahead. Authentication of a diagnostic image obtained from a specialist at a remote location which is from the sender is one of the most challenging tasks in an automated healthcare setup. Intruders were found to be able to efficiently exploit securely transmitted messages from previous literature since the algorithms were not efficient enough leading to distortion of information. Therefore, this study proposed a modified least significant bit (LSB) technique capable of protecting and hiding medical data to solve the crucial authentication issue. The application was executed and established by utilizing MATLAB 2018a, and it used a logical bit shift operation for execution. The investigational outcomes established that the proposed technique can entrench medical information without leaving a perceptible falsification in the stego image. The result of this implementation shows that the modified LSB image steganography outperformed the standard LSB technique with a higher PSNR value and lower MSE value when compared with previous research works. The number of shifts was added as a new performance metric for the proposed system. The study concluded that the proposed secured medical information system was evidenced to be proficient in secreting medical information and creating undetectable stego images with slight entrenching falsifications when likened to other prevailing approaches.

Current Status of a Medical Information System

1970 ◽  
Vol 09 (03) ◽  
pp. 149-160 ◽  
Author(s):  
E. Van Brunt ◽  
L. S. Davis ◽  
J. F. Terdiman ◽  
S. Singer ◽  
E. Besag ◽  
...  
Keyword(s):  
Information System ◽  
Medical Records ◽  
Medical Information ◽  
Clinical Laboratory ◽  
Development Program ◽  
Medical Data ◽  
Direct Access ◽  
Medical Information System ◽  
Current Status ◽  
Central System

A pilot medical information system is being implemented and currently is providing services for limited categories of patient data. In one year, physicians’ diagnoses for 500,000 office visits, 300,000 drug prescriptions for outpatients, one million clinical laboratory tests, and 60,000 multiphasic screening examinations are being stored in and retrieved from integrated, direct access, patient computer medical records.This medical information system is a part of a long-term research and development program. Its major objective is the development of a multifacility computer-based system which will support eventually the medical data requirements of a population of one million persons and one thousand physicians. The strategy employed provides for modular development. The central system, the computer-stored medical records which are therein maintained, and a satellite pilot medical data system in one medical facility are described.

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.

scholarly journals Optimal Image Steganography Content Destruction Techniques

2021 ◽  
Vol 15 ◽  
pp. 84-88
Author(s):  
Siddeeq Y. Ameen ◽  
Muthana R. Al-Badrany
Keyword(s):  
Discrete Cosine Transform ◽  
Image Steganography ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Least Significant Bit ◽  
Hidden Information ◽  
Random Data ◽  
Cosine Transform ◽  
Wavelet Techniques ◽  
Lsb Technique

The paper presents two approaches for destroying steganogrphy content in an image. The first is the overwriting approach where a random data can be written again over steganographic images whereas the second approach is the denoising approach. With the second approach two kinds of destruction techniques have been adopted these are filtering and discrete wavelet techniques. These two approaches have been simulated and evaluated over two types of hiding techniques, Least Significant Bit LSB technique and Discrete Cosine Transform DCT technique. The results of the simulation show the capability of both approaches to destroy the hidden information without any alteration to the cover image except the denoising approach enhance the PSNR in any received image even without hidden information by an average of 4dB.

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 Innovative Region Based Steganographic Technique to Provide Security and Authentication to Digital Image

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3706-3710
Keyword(s):  
Mean Square Error ◽  
Digital Image ◽  
Image Steganography ◽  
The Internet ◽  
Main Concern ◽  
Mean Square ◽  
Least Significant Bit ◽  
Lsb Technique ◽  
Intended Receiver

In this advanced world with the growing technology, the demand for security of information is needed in any communication streams of data which is being conveyance from host to intended host over the internet. Obviously, a huge & numerous amount of the data or the information are transferred in our everyday. So, the demand for securing information has become the main concern. Image Steganography is one of the important areas in the field of Steganography. The main purpose of steganography is to protect the surreptitious information from others except from intended receiver & by increasing the security of the covert data in the significant way that information can’t be revealed although the intruder knows the methodology of the embedding process. In this paper, The aim is to propose a different yet, an innovative steganographical technique which provides the security on our digital image, and by using a quality measuring technique like Mean Square Error(MSE), Peak Signal Noise Ratio (PSNR) which assure the quality of image has been not degraded even after infusing the covert data inside the image. So to overcome these issues, this paper, suggests a new method to maintain the quality of the image. After embedding the authenticated information in the cover image using Region-Based Least Significant Bit (LSB) technique that provides security of digital image

scholarly journals PERBAIKAN ALGORITMA STEGANOGRAFI TEKNIK LEAST SIGNIFICANT BITS UNTUK APLIKASI KEAMANAN DATA

2018 ◽  
Vol 3 (1) ◽  
pp. 27-32
Author(s):  
Tika Erna Putri ◽  
Muhammad Rifqi Al Fauzan ◽  
Prima Asmara Sejati
Keyword(s):  
Digital Media ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Third Party ◽  
Security Level ◽  
Least Significant Bit ◽  
Stego Image ◽  
Security Issues ◽  
Squared Error ◽  
Lsb Technique

Security issues have become major problem in the field of data communications, specifically in the data transmission through the internet. One of the solutions is to hide the messages through a digital media so the attention of the attacker or third party can be avoided, this method is known as steganography. In this research, we use images as digital media. We modify the Least Significant Bit (LSB) which is the most commonly used technique in steganography. Unfortunately LSB has poor security level since it is already widely known technique. Therefore, it is important to modify the algorithm of LSB to ensure its security aspect. An improvement to LSB technique is suggested by selecting only odd pixels and ignoring even pixels in the implementation of steganography. We successfully implement the modified LSB algorithm by using RBG image and grayscale image as steganography media. Mean Squared Error (MSE) and Peak Signal-to-noise Ratio (PSNR) are employed to evaluate the stego-image quality. Our calculations show that the modified LSB algorithm provides better results than the conventional LSB. The conventional LSB algorithm gives 1.98 10-5 for MSE and 95.20893 dB for PSNR calculations, while the modified LSB gives 1. 80 10-5 and 95.6101 dB for MSE and PSNR, respectively.

Multilevel Secure Digital Image Steganography Framework Using Random Function and Advanced Encryption Standard

2019 ◽  
Vol 16 (11) ◽  
pp. 4812-4825
Author(s):  
Mohsin N. Srayyih Almaliki
Keyword(s):  
Image Quality ◽  
Random Function ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Secret Message ◽  
Least Significant Bit ◽  
Signal To Noise ◽  
Stego Image ◽  
Preparation Phase ◽  
Noise Ratio

One of the crucial aspects of processes and methodologies in the information and communication technology era is the security of information. The security of information should be a key priority in the secret exchange of information between two parties. In order to ensure the security of information, there are some strategies which are used, and they include steganography and cryptography. With cryptography, the secret message is converted into unintelligible text, but the existence of the secret message is noticed, nonetheless, steganography involves hiding the secret message in a way that its presence cannot be noticed. In this paper, a new secure image steganography framework which is known as an adaptive stego key LSB (ASK-LSB) framework is proposed. The construction of the proposed framework was carried out in four phases with the aim of improving the data-hiding algorithm in cover images by using capacity, image quality, and security. To achieve this, the Peak Signal-to-Noise Ratio (PSNR) of the steganography framework was maintained. The four phases began with the image preparation phase, followed by the secret message preparation phase, embedding phase and finally extraction phase. The secure image steganography framework that is proposed in this study is based on a new adaptive of least significant bit substitution method, combination random function, and encryption method. In the proposed work, the secret bits are inserted directly or inversely, thereby enhancing the imperceptibility and complexity of the process of embedding. Results from the experiment reveal that the algorithm has better image quality index, peak signal-to-noise ratio, and payload used in the evaluation of the stego image.

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 Medical Sports Data Privacy Protection Method Based on Legal Risk Control

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Liqiang Jia ◽  
Wei Fan
Keyword(s):  
Data Privacy ◽  
Medical Information ◽  
Risk Control ◽  
Medical Data ◽  
Medical Information System ◽  
Legal Risk ◽  
Medical Environment ◽  
Data Privacy Protection ◽  
Improved Model ◽  
Sports Data

With the continuous development of computer and network technology, the amount of information storage in medical information system is more and more large, which is prone to the problem of privacy information leakage, resulting in irreparable harm. In order to solve the problem of privacy leakage in the medical environment, a new privacy rating method is proposed according to the actual situation of the medical environment. The big data technology is used to effectively mine, analyze, integrate, and reuse medical data, and a new improved model is proposed. At the same time, the medical information system applying the improved model is designed according to the complex actual needs. The purpose of this paper is to correctly understand the positive role of medical sports big data (BD) research in the medical field and standardize the behavior of medical staff. On the one hand, it can improve the safety awareness of patients and enhance the standardization of medical treatment environment. This paper will analyze the meaning and research status of medical data from the perspective of legal risk control, focus on the status quo and existing problems of medical sports data privacy protection, and put forward positive countermeasures and some practical solutions. The results show that the medical sports information data has certain regularity and particularity, ease to spread, and mining. Hospitals and medical staff should make the areas and items restricted by law clear, standardize their own behaviors, constantly sum up experience, and actively improve and modify relevant measures.

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