Шифрування цифрових медичних зображень у програмах реального часу
Patient information and medical imaging data are now subject to stringent data security and confidentiality standards due to the proliferation of telemedicine techniques and medical imaging instruments. Because of the problems described above, as well as the possibility of data or information being...
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| author | Abboud, Izz Al-Rawi, Muaayed Al-Awad, Nasir |
| author_facet | Abboud, Izz Al-Rawi, Muaayed Al-Awad, Nasir |
| author_institution_txt_mv | [
{
"author": "Izz Abboud",
"institution": "Mustansiriyah University, Baghdad"
},
{
"author": "Muaayed Al-Rawi",
"institution": "Mustansiriyah University, Baghdad"
},
{
"author": "Nasir Al-Awad",
"institution": "Mustansiriyah University, Baghdad"
}
] |
| author_sort | Abboud, Izz |
| baseUrl_str | http://journal.iasa.kpi.ua/oai |
| collection | OJS |
| datestamp_date | 2024-05-23T07:09:36Z |
| description | Patient information and medical imaging data are now subject to stringent data security and confidentiality standards due to the proliferation of telemedicine techniques and medical imaging instruments. Because of the problems described above, as well as the possibility of data or information being stolen, this brings up the dilemma of transmitting data on medical images via an open network. In the past, potential solutions included the utilization of methods such as information concealment and image encryption. Nevertheless, attempting to reconstruct the original image utilizing these approaches may result in complications. In the process of this paper, an algorithm for safeguarding medical images based on the pixels of interest was established. Detection of image histogram peaks for the purpose of calculating peaks in medical images pixels of interest in medical image that have had their threshold values processed. The threshold is shown by taking the average of all the peaks in the histogram. After that, a Sudoku matrix is used to assign values of interest to each of these pixels. The proposed method will be assessed by a variety of statistical procedures, and the outcomes of these analyses will be compared to previously established standards. According to the findings, the suggested method has superior security performance compared to other image encryption methods already in use. |
| doi_str_mv | 10.20535/SRIT.2308-8893.2024.1.02 |
| first_indexed | 2025-07-17T10:28:12Z |
| format | Article |
| fulltext |
Izz K. Abboud, Muaayed F. Al-Rawi, Nasir A. Al-Awad, 2024
26 ISSN 1681–6048 System Research & Information Technologies, 2024, № 1
UDC 62-50
DOI: 10.20535/SRIT.2308-8893.2024.1.02
DIGITAL MEDICAL IMAGE ENCRYPTION APPROACH
IN REAL-TIME APPLICATIONS
IZZ K. ABBOUD, MUAAYED F. AL-RAWI, NASIR A. AL-AWAD
Abstract. Patient information and medical imaging data are now subject to stringent
data security and confidentiality standards due to the proliferation of telemedicine
techniques and medical imaging instruments. Because of the problems described
above, as well as the possibility of data or information being stolen, this brings up
the dilemma of transmitting data on medical images via an open network. In the
past, potential solutions included the utilization of methods such as information con-
cealment and image encryption. Nevertheless, attempting to reconstruct the original
image utilizing these approaches may result in complications. In the process of this
paper, an algorithm for safeguarding medical images based on the pixels of interest
was established. Detection of image histogram peaks for the purpose of calculating
peaks in medical images pixels of interest in medical image that have had their
threshold values processed. The threshold is shown by taking the average of all the
peaks in the histogram. After that, a Sudoku matrix is used to assign values of inter-
est to each of these pixels. The proposed method will be assessed by a variety of sta-
tistical procedures, and the outcomes of these analyses will be compared to previ-
ously established standards. According to the findings, the suggested method has
superior security performance compared to other image encryption methods already
in use.
Keywords: real time applications, medical images, encryption, security, peak detection.
INTRODUCTION
Because of increased and better investment in multimedia techniques, research
pertaining to medical imaging has made great strides forward in recent years. The
vital personal information that the patient wishes to keep private is included in the
medical image. In order to safeguard sensitive information, medical images are
often encrypted. Textual data is often encrypted via one of many standard algo-
rithms, including Advanced Encryption Standard (AES), Data Encryption Stan-
dard (DES), International Data Encryption Algorithm (IDEA), or Triple DES.
Other frequent encryption techniques include the pixels in medical images are not
evenly distributed, and the data has a high resolution. There are also distinct geo-
graphical patterns. Due to the slowness of bulk data, traditional encryption is not
an appropriate method for safeguarding images from digital imaging and commu-
nication systems (DICOM) in the field of medical care.
RELATED WORK
When medical professionals require more information to diagnose a patient,
medical imaging provides a secondary source of information that is both vital and
effective [1]. Unfortunately, the fastest way to transmit medical images (and the
one that is often considered to be the most effective) is typically over open net-
Digital medical image encryption approach in real-time applications
Системні дослідження та інформаційні технології, 2024, № 1 27
works like sharing files and email. Images that have been sent in this manner are
at risk of being subject to actions such as content alteration, illicit duplication, and
the loss of copyright [2]. As a direct consequence of this, there has been an in-
crease in the number of studies into medical image security that focus on image
encryption and information concealment [3]. The article [4] provided an explana-
tion of an approach that was not only simple but also effective. It included utiliz-
ing matrix multiplication to change the pixel values in an image, which resulted in
a fairly straightforward process but made it very difficult for unauthorized indi-
viduals to extract the information contained in the images. A combination of a
logistic map and a 3D Lorenz, both of which displayed multiple operating modes,
was essentially what produced the 5-D hyper chaotic map that was mentioned in
the study [5]. While one of the modes concentrates only on the pixels that are de-
rived from images with clear text, the other option diffuses the light a total of two
times in order to produce images that are secured. Because of the study that
solved the security problem [6], it is now possible for online users’ sensitive data
to be exchanged on web apps without the users’ needing to worry about their pri-
vacy being compromised. Article [7] developed a 1-D chaotic map in order to get
additional security by recognizing its shortcomings. This was followed by the
presentation of a modified version of the plain text attack. Paper [8] revealed the
hidden data that was hiding in a portion of the image by picking an essential sec-
tion of a medical image, which is something that is often done by choosing the
portions of the image that are utilized more frequently. In article [9], a method for
partially encrypting secret data contained in photographs was presented, with FF1
and FF3-1 serving as key components.
The sensitive information will be encrypted without leading to an increase in
the file size, which might result in a loss of memory. The gray scale encryption
method based on Image Region of Interest (ROI) with chaos is presented in article
[10]. To begin, the portion of the ROI that has to be recognized must be done so
utilizing the Sobel edge detection technique. The edges of the blocks must then be
used to sort the components of the image into those that are significant and those
that are not essential. Sine maps are utilized to encrypt the irrelevant area,
whereas the Lorenz method is utilized to encrypt the region that contains the ROI.
Paper [11] provides a self-generating area of interest (ROI) approach for water-
marking applications in biological images. The most significant benefit that this
approach has over others is that it is secure enough to avoid a wide variety of at-
tacks, including those using Gaussian, median, sharpening, and wiener filters. Re-
search [12] addressed a new approach in which he showed how to identify the
ROI with perfect precision, how to prevent information leakage in the ROI sec-
tion, and how to retrieve the information lossless from encryption in the transform
domain. This approach was presented as part of the discussion of the new ap-
proach. Therefore, here we come across a unique lossless game theory based
medical image encryption approach with optimal ROI parameters in addition to
ROI concealed locations. This method was developed in this work. In order to
retrieve the medical picture without losing any data, the process of encryption
must first entail a transformation at the pixel level of the ROI. This is done to
safeguard the loss of information contained within the medical image. The chaos-
based encryption approaches covered in the article [13] make use of a variety of
different encryption algorithms. The article [14] suggested an enhanced histogram
shifting (HS) reversible watermark technique for medical images and others’
work in order to increase the hidden capacity of the algorithm. For the purpose of
embedding information utilizing the HS technique, an image should be cut up into
Izz K. Abboud, Muaayed F. Al-Rawi, Nasir A. Al-Awad
ISSN 1681–6048 System Research & Information Technologies, 2024, № 1 28
smaller parts. The authors of article [15] place a high priority on integrating in-
formation into texture regions via the use of HS and contrast enhancement, with
the goals of enhancing contrast in texture areas and improving how the image is
subjectively perceived. In the study by [16], the authors preserved patient infor-
mation by using a reversible image masking strategy for HS. After that, they en-
hance image quality by using two parameters of linear prediction: weight and
threshold. The economy and the interest rate merged. Research [17] suggests us-
ing an HS technique to look into the lossless data that high-resolution medical
images conceal. Employ a strong correlation in the image’s local block pixels for
the purpose of rendering the smooth surface of the medical imaging anatomy. It is
not difficult at all to modify the capacity and the signal-to-noise ratio (PSNR) in
accordance with the block size, the partition level, and the number of embedded
bits. Many of the objectives of the aforementioned approaches include ensuring
that the image is protected from infringement on its copyright and minimizing the
amount of distortion in the visual quality of the embedded image. Image histo-
gram peak detection is a basic approach for digital image processing that may be
used directly and efficiently for image segmentation, quality evaluation, en-
hancement, decrease in data, and other purposes. It is also one of the most impor-
tant aspects of digital image processing.
SUDOKU MATRIX
A Sudoku matrix is denoted by the notation X × X and may include any number
between 1 and N. However, given that X is the square of the number and N equals
X, each number can only appear once in each row of the matrix. Only the first
value in each column and the first value in each block will be increased. The fol-
lowing illustration in Fig. 1 provides a sample of a Sudoku problem as well as the
answer for X = 9. The result of successfully solving a Sudoku problem is referred
to as the “Sudoku matrix”.
Sudoku Typical Sudoku problems are derived from the Sudoku Matrix by
omitting some cells, but each problem also includes hints on how to solve it on its
own. The researchers have made an effort to come up with a number of different
solutions. In this piece, we will construct a Sudoku matrix via the use of a tech-
nique called the Latin square. The downside of this rapid and systematic tech-
nique is that the set of Sudoku matrices that it generates is just a subset of the uni-
versal set of all possible Sudoku matrices. This is a limitation of the method, but it
does not prevent it from being useful.
Fig. 1. A sample Sudoku puzzle and its solution: a — Row#, Column # and Block# nota-
tion; b — a sample Sudoku puzzle; c — the solution to Sudoku puzzle (b)
a b c
Digital medical image encryption approach in real-time applications
Системні дослідження та інформаційні технології, 2024, № 1 29
PROPOSED ENCRYPTION SELECTIVE METHOD
Fig. 2 presents the block diagram of the proposed selective image encryption
method. The proposed method is comprised of a number of processes that, in or-
der to identify and encrypt the area of interest in the medical image, are neces-
sary. The first step is to calculate the histogram peak of the original image using
the formula presented in Fig. 3. The peak detection method uses the image histo-
gram to first create a peak detection signal. The extrema that are between the zero
and zero intersections of the peak detection signal are then used in order to locate
the peaks that are present in the histogram. A close approximation of the first de-
rivative may be achieved using convolution by utilizing a differentiator. The peak
may be identified in a histogram that has ideal smoothness by locating the point
where the sign and zero intersection of the signal that was produced by the h and
S convolutions occur. The extrema of the histogram and the location of the turn-
ing point may be estimated using the zero intersection method. The peak values of
the original medical imaging are shown by the symbol “*” in Fig. 3. The thresh-
old value for separating the relevant pixels in a medical image may be derived by
taking the average of all the peak values that are acquired via the use of the histo-
gram peak detection function. The next step is to examine each pixel in the origi-
nal medical image against the predetermined threshold value; if the value is
higher, the pixels must be grouped together to form a meaningful pixel block. The
diffusing procedure is performed on a Sudoku matrix consisting of numerous ran-
dom 16*16 grids. Perform an XOR operation on the significant pixel block using
the pixels in the Sudoku matrix to generate a random encryption of the block.
c
Fig. 2. The architecture of proposed visible image encryption method
Fig. 3. Original MRI image — a; Peak detection using histogram — b
a
b
Pixel Value
N
um
be
r
of
P
ix
el
s
Izz K. Abboud, Muaayed F. Al-Rawi, Nasir A. Al-Awad
ISSN 1681–6048 System Research & Information Technologies, 2024, № 1 30
SIMULATION AND RESULT DISCUSS OF THE PROPOSED METHOD
By simulating the proposed encryption selective method on a PC using MatLab,
images are transferred after the medical image has been encrypted. When trans-
ferring the medical image, we transfer the encrypted image to protect the original
medical image. This is possible because the only person who will be able to view
the original after this process is the person to whom we want to transfer the im-
age. After the decryption procedure of the encrypted medical image, the original
image is only sent to that specific person. Fig. 4 displays the original Magnetic
Resonance Imaging (MRI) with its encryption image. Once an image has been
encrypted, the original image cannot be reconstructed until the encryption process has
been completed correctly. In a similar fashion, Fig. 5 and Fig. 6 display the original
image as well as the encrypted version of the hand and leg images respectively.
Fig. 4. The input MRI image and corresponding ROI encrypted MRI image
Fig. 5. The input hand image and corresponding ROI encrypted hand image
Fig. 6. The input leg image and corresponding ROI encrypted leg image
Digital medical image encryption approach in real-time applications
Системні дослідження та інформаційні технології, 2024, № 1 31
CONCLUSION
In this paper, we present a method for partially encrypting personal data, such as
tumors in the brain, hand parts, and so on. Padding and a rise in data volume as a
result of wasted storage space over time are challenges that are inherent to tradi-
tional image protection systems. Additionally, since the whole image is en-
crypted, it cannot be recognized before it is decrypted, and when it is decrypted,
critical information is revealed. The difficulty with conventional sub-image en-
cryption is that it encrypts superfluous sections by first encrypting a rectangular
region that covers information that has to be kept private. This issue can now be
resolved via the technique that was suggested. The suggested approach encrypts
the data using a Sudoku matrix after it has been used to determine the important
pixels using a histogram peak detection approach.
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Izz K. Abboud, Muaayed F. Al-Rawi, Nasir A. Al-Awad
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15. M. Li, D. Lu, and W. Wen, “Cryptanalyzing a color image encryption scheme based
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Received 16.06.2023
INFORMATION ON THE ARTICLE
Izz K. Abboud, ORCID: 0000-0002-8344-8585, Mustansiriyah University, Iraq, e-mail:
izz_kadhum@uomustansiriyah.edu.iq
Muaayed F. Al-Rawi, ORCID: 0000-0003-1841-1222, Mustansiriyah University, Iraq, e-
mail: muaayed@uomustansiriyah.edu.iq
Nasir A. Al-Awad, ORCID: 0000-0003-3059-4375, Mustansiriyah University, Iraq, e-
mail: nasir.awad@uomustansiriyah.edu.iq
ШИФРУВАННЯ ЦИФРОВИХ МЕДИЧНИХ ЗОБРАЖЕНЬ У ПРОГРАМАХ
РЕАЛЬНОГО ЧАСУ / Ізз К. Аббуд, Муаайед Ф. Аль-Раві, Насір А. Аль-Авад
Анотація. Інформація про пацієнтів і дані медичних зображень тепер підпа-
дають під дію суворих стандартів безпеки даних і конфіденційності, що є пря-
мим результатом поширення телемедичних методів й інструментів для медич-
них зображень. Через зазначені проблеми, а також через можливість
викрадення даних або інформації, виникає дилема передавання даних на меди-
чні зображення через відкриту мережу. У минулому потенційні рішення вклю-
чали в себе використання таких методів, як приховування інформації та шиф-
рування зображень. Тим не менше спроба реконструювати оригінальне
зображення за допомогою цих підходів може призвести до ускладнень. У ході
роботи створено алгоритм для захисту медичних зображень на основі пікселів
інтересу. Виявлення піків гістограми з метою обчислення піків у медичних зо-
браженнях пікселів інтересу медичних зображеннях, для яких оброблені поро-
гові значення. Порогове значення відображається як середнє значення усіх пі-
ків на гістограмі. Після цього застосовується матриця Sudoku для призначення
значень інтересу кожному з цих пікселів. Запропонований метод оцінено за
допомогою різноманітних статистичних процедур, а результати цих аналізів
порівняно з раніше встановленими стандартами. Згідно з висновками, запро-
понований метод має кращу ефективність безпеки порівняно з іншими вже ви-
користовуваними методами шифрування зображень.
Ключові слова: додатки реального часу, медичні зображення, шифрування,
безпека, виявлення піків.
|
| id | journaliasakpiua-article-281461 |
| institution | System research and information technologies |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2025-07-17T10:28:12Z |
| publishDate | 2024 |
| publisher | The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" |
| record_format | ojs |
| resource_txt_mv | journaliasakpiua/78/d9c681773010c1e79dee2d1a38022678.pdf |
| spelling | journaliasakpiua-article-2814612024-05-23T07:09:36Z Digital medical image encryption approach in real-time applications Шифрування цифрових медичних зображень у програмах реального часу Abboud, Izz Al-Rawi, Muaayed Al-Awad, Nasir real time applications medical images encryption security peak detection додатки реального часу медичні зображення шифрування безпека виявлення піків Patient information and medical imaging data are now subject to stringent data security and confidentiality standards due to the proliferation of telemedicine techniques and medical imaging instruments. Because of the problems described above, as well as the possibility of data or information being stolen, this brings up the dilemma of transmitting data on medical images via an open network. In the past, potential solutions included the utilization of methods such as information concealment and image encryption. Nevertheless, attempting to reconstruct the original image utilizing these approaches may result in complications. In the process of this paper, an algorithm for safeguarding medical images based on the pixels of interest was established. Detection of image histogram peaks for the purpose of calculating peaks in medical images pixels of interest in medical image that have had their threshold values processed. The threshold is shown by taking the average of all the peaks in the histogram. After that, a Sudoku matrix is used to assign values of interest to each of these pixels. The proposed method will be assessed by a variety of statistical procedures, and the outcomes of these analyses will be compared to previously established standards. According to the findings, the suggested method has superior security performance compared to other image encryption methods already in use. Інформація про пацієнтів і дані медичних зображень тепер підпадають під дію суворих стандартів безпеки даних і конфіденційності, що є прямим результатом поширення телемедичних методів й інструментів для медичних зображень. Через зазначені проблеми, а також через можливість викрадення даних або інформації, виникає дилема передавання даних на медичні зображення через відкриту мережу. У минулому потенційні рішення включали в себе використання таких методів, як приховування інформації та шифрування зображень. Тим не менше спроба реконструювати оригінальне зображення за допомогою цих підходів може призвести до ускладнень. У ході роботи створено алгоритм для захисту медичних зображень на основі пікселів інтересу. Виявлення піків гістограми з метою обчислення піків у медичних зображеннях пікселів інтересу медичних зображеннях, для яких оброблені порогові значення. Порогове значення відображається як середнє значення усіх піків на гістограмі. Після цього застосовується матриця Sudoku для призначення значень інтересу кожному з цих пікселів. Запропонований метод оцінено за допомогою різноманітних статистичних процедур, а результати цих аналізів порівняно з раніше встановленими стандартами. Згідно з висновками, запропонований метод має кращу ефективність безпеки порівняно з іншими вже використовуваними методами шифрування зображень. The National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" 2024-03-29 Article Article application/pdf https://journal.iasa.kpi.ua/article/view/281461 10.20535/SRIT.2308-8893.2024.1.02 System research and information technologies; No. 1 (2024); 26-32 Системные исследования и информационные технологии; № 1 (2024); 26-32 Системні дослідження та інформаційні технології; № 1 (2024); 26-32 2308-8893 1681-6048 en https://journal.iasa.kpi.ua/article/view/281461/296285 |
| spellingShingle | додатки реального часу медичні зображення шифрування безпека виявлення піків Abboud, Izz Al-Rawi, Muaayed Al-Awad, Nasir Шифрування цифрових медичних зображень у програмах реального часу |
| title | Шифрування цифрових медичних зображень у програмах реального часу |
| title_alt | Digital medical image encryption approach in real-time applications |
| title_full | Шифрування цифрових медичних зображень у програмах реального часу |
| title_fullStr | Шифрування цифрових медичних зображень у програмах реального часу |
| title_full_unstemmed | Шифрування цифрових медичних зображень у програмах реального часу |
| title_short | Шифрування цифрових медичних зображень у програмах реального часу |
| title_sort | шифрування цифрових медичних зображень у програмах реального часу |
| topic | додатки реального часу медичні зображення шифрування безпека виявлення піків |
| topic_facet | real time applications medical images encryption security peak detection додатки реального часу медичні зображення шифрування безпека виявлення піків |
| url | https://journal.iasa.kpi.ua/article/view/281461 |
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