An Efficient Multilayer approach for Securing E-Healthcare Data
in Cloud using Crypto – Stego Technique
NAGAMANY ABIRAMI1 , M.S. ANBARASI2
1Department of Computer Science and Engineering, Puducherry Technological University
Puducherry, INDIA
2Department of Information Technology, Puducherry Technological University
Puducherry, INDIA
Abstract: — Healthcare data has been moving to cloud platforms in recent years, which has increased accessibility and
scalability but also raised security issues. Ensuring data integrity and safeguarding private health information from
unwanted access are critical. This paper presents a comprehensive strategy to integrate effective Elliptic Curve
Cryptography ECC-AES with steganography techniques to improve the security of healthcare data in the cloud. ECC-
AES is especially well-suited for cloud situations with limited resources since it provides strong security with reduced
key sizes. Confidentiality is guaranteed by encrypting healthcare data using ECC- AES before storage, reducing the
possibility of data breaches. Steganography techniques are also integrated to improve security against skilled adversaries
by adding an extra degree of obfuscation by concealing encrypted data inside innocuous files or images. Strict key
management procedures, access control systems, and frequent security audits are important components of the proposed
system that ensure adherence to Health Insurance Portability and Accountability Act (HIPAA) and General Data
Protection Regulation (GDPR) compliance requirements pertaining to healthcare data protection. Programs for employee
awareness and training are also crucial for reducing the likelihood of human mistakes. Healthcare businesses can safely
use cloud technology while protecting patient data integrity and privacy by putting in place multi-layered security
safeguards. The proposed system provides the multilayer security on healthcare data in cloud environment than other
existing systems.
Key-words—ECC, AES, Healthcare Data, Cloud Computing, Cryptography, Steganography, Encryption, Data Privacy
Received: March 14, 2024. Revised: August 17, 2024. Accepted: September 15, 2024. Published: October 14, 2024.
1. Introduction
The spectrum of completely integrated services and
solutions that satisfy various socio-industrial demands
has expanded due to the exponential rise of software and
sophisticated hardware systems. Out of all the most
recent emergent applications, data transmission and its
allied forces in the exchange of knowledge have
garnered widespread favour worldwide [1]. However,
the rapid advancement of internet technology and its
associated applications has given rise to a number of
breakthroughs, including cloud computing and the
Internet of Things (IoT). However, companies have
traditionally faced difficulties in guaranteeing safe
communication across diverse application contexts [2].
Many communication technologies that enable the
Internet are used on a daily basis for a variety of
purposes, including social networking sites, the medical
services industry, e-commerce, Organizations of
scientific community, the business sector, and many
other industrial demands like monitoring and security
systems [3].
Data transmission was transformed by the increased
bandwidth and data rates of optical fiber communication
and 4G/5G cellular technology. Data communication
over the internet in the form of text, photos, audio, and
video is now commonplace [4]. Governments, Agencies
of law enforcement, and hospitals are exchanging
multimedia data for telemedicine purposes. There was
an increase in internet traffic throughout the lockdown in
worldwide at the time of the COVID-19.Despite the fact
that using the internet has many benefits, security and
data privacy are still problems [5]. Hackers may now
access a wide range of tools, data theft, modifications,
and revisions are now feasible. As a result, maintaining
data security has emerged as a difficult yet crucial
problem for researchers. To solve data security
challenges, a variety of information-protecting
procedures have been proposed, including data
concealing techniques and cryptography. Cryptography
disintegrates and transforms the confidential information
into a format that is unintelligible to an unapproved
individual. Standard encryption methods or chaos-based
encryption methods can be used for cryptography. Prior
to embedding, the crucial data in these methods is
encrypted using the secret key. However, the primary
drawback of SETs—which renders them unreliable and
unsecure for data encryption—is the volume of data with
key lengths [6].
The chaos-based encryption techniques have helped
to overcome the SETs' drawback. The original
encryption keys used in the chaos encryption approach
are susceptible to modifications. Therefore, more safe
cryptographic techniques to guarantee data security are
chaos-based encryption schemes. By using encryption to
alter the original data's shape, cryptography can offer a
high level of data security. However, cryptography by
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itself is not impervious to security breaches because its
encrypted form draws the attention of attackers and can
thus be altered or compromised [7]. Encrypted shape
could attract the curiosity of an eavesdropper; it is not a
suitable way to ensure data security. As a result, data
masking has been extensively employed by academics to
conceal the presence of crucial data to stop drawing the
attention of outsiders [8].
The IoT has advanced to the point that almost
anything may be accessible at any time, from any
location, and can perform almost any function. In order
to enable cooperative computing scenarios, the IoT is
typically made up of small components that are
connected to one another. The cost of energy,
connection of devices and processing power are some of
the IoT's constraints. Medical devices ability to integrate
IoT capabilities which improves service quality and
efficiency, the healthcare industry has adopted IoT at a
faster pace than others [9].
S-health, or smart health, is the situational
enhancement of telehealth in intelligent cities, allowing
for accurate and effective prevention of illness and
accidents. Recently, the disease-centered approach by
healthcare management has given way to the patient-
centered approach globally. Because of how simple it is
to handle and distribute health data, it has become
ingrained in the medical industry. It allowing for
continual monitoring of physiological conditions, long-
term illness proposed, and therapy instruction [10].
Up until that point, s-health can reduce medical costs
and raise the standard of service. Even though s-health is
still in its early stages, a lot of problems still need to be
resolved before it can be applied in practical situations.
Individuals are becoming increasingly concerned about
hacking attempts in the s-health industry and
safeguarding the confidentiality and safety of highly
sensitive individual healthcare information of the IoT
users without sacrificing the data's usefulness remains a
difficulty [11]. However, most access control systems
only offer coarse-grained access limits or undermine
data security. According to this logic, end-to-end data
secrecy can be secured using sharing key mechanisms,
but they are insufficient in these novel situations. This
feature specifies the conditions that a subject needs to
fulfill in order to fully decode a piece of data [12].
Examined the creation of a homomorphic encryption
algorithm for the first time in that year. Numerous
attempts by scholars to design homomorphic systems
with different operations led to the development of this
idea. Homomorphic encryption is a collection of
encryption methods that can be used for a variety of
computations on encrypted data. Some of the most
common forms of homomorphic encryption include
leveled fully homomorphic, partially homomorphic,
slightly homomorphic, and absolutely homomorphic. It
is possible to do an infinite number of tasks at once with
Fully Homomorphic Encryption (FHE). IoT systems
need to adhere to stronger security and dependability
standards to safeguard people's privacy and
confidentiality [13].
No matter its origin or geographic barriers, cloud
computing offers real-time computing, data access, and
cloud-based decision-making to a wide range of
stakeholders. This is one of its primary characteristics.
However, until a strong security mechanism is offered,
information exchanged between nodes, between users,
or throughout the cloud platform is extremely insecure.
One of the main issues with cloud computing is how to
securely communicate or preserve personal data,
especially multimedia (audio, video, and image) [14].
Enabling computational effectiveness is also necessary,
as cloud computing necessitates fast and dependable
processing to fulfill real-time application requirements.
This is in addition to ensuring secure communication
[15]. In light of the rapidly increasing needs for
computing power and related communication, it
represents the guarantee of security, scalability, and
manageability in the cloud computing environment. In
cloud environments such as social networking,
healthcare, etc., facilitating data security has become
essential. The intricate architecture of cloud
deployments faces serious risks from a loss of vision and
control. A more sophisticated security strategy is also
required since the elastic boundary of cloud usage
causes the security perimeter to constantly shift [16].
2. Literature Survey
Pay-as-you-go model, the cloud makes use of
technologies like cryptography and steganography for
safeguarding user data transfer. The Least Significant
Bit (LSB) and Discrete Cosine Transform (DCT)
techniques were the main topics of this work's review of
numerous investigations [17]. The author’s primary
concern is the hybrid approach combining AES and
FHE. Unlike earlier methods, this hybrid strategy is
safer, more redundant, and lets the user preserve data.
They believe that if AES can encrypt data with 14 cycles
using a 256-piece square, then, cloud computing may be
able to benefit from this breakthrough as well. A FHE
technique serves as the foundation for the second phase's
encryption process. Two objectives are achieved by this
method: multiplicative homomorphic and additional
substance. Only the newly added substance calculations
will be utilized by the user. The user is using the private
key given that they possess the cipher text obtained
through maiden scrambling. The secret key and the
content of the Cipher will now be encrypted jointly
using additional material homomorphic encryption. The
user may safeguard privacy, confidentiality of data, and
integrity of data from hackers by employing this method
[18].
According to the authors of this paper, encryption
makes it possible to send sensitive data across an
unprotected channel without running the danger of it
being lost or altered by unwanted parties [19]. ECC
requires a very tiny key, it is utilized in this paper to
encipher data on the cloud. Elliptic Curve uses the least
amount of energy since its small key size minimizes
computing power. In this work, ECC is used for key
production, encryption, and decryption. The report
suggests a two-tiered approach to cloud data protection.
The data must first be divided into manageable portions
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Volume 6, 2024
before being encrypted using randomized safe curves. A
quantum computing system might may not be in
position to compromise data security when the two
stages are completed .
Value, Variety, Velocity, Veracity, and Volume—
the five Vs.—all need to be taken into account in the
healthcare industry since a variety of data, including
patient names, birthdates, and vital sign numbers, are
frequently collected and must be kept on file for several
systems. Daily data collection would produce high
velocity, which would cause the volume of data to
expand quickly [20]. In a recent study that assessed the
variety and volume of health information, developed a
digital memory system supporting essential medical
services. Its goal is to organize various biological
records in an emergency situation and make them easily
accessible to the necessary medical personnel [21].
On encrypted data, unrestricted computations such as
additions and multiplications are obtainable by FHE
producing results that, when decrypted, are exactly akin
to the operations on plain data. As a result, cloud
infrastructure can function lawfully using encrypted data
without requiring any prior decoding [22].
Homomorphic technology began in 1978 with the
introduction of asymmetric encryption, and it was who
initially presented the concept of homomorphic
encryption. RSA is a partial homomorphic method
which solely considers operations that are multiplicative
[23].
The deficiency in current research is the absence of a
thorough security framework that is especially designed
to meet the special needs of healthcare data in cloud
systems. Although there is a wealth of literature on
cryptography and general cloud security, there is a
conspicuous lack of research that focuses explicitly on
tackling the security concerns associated with processing
and storing healthcare data in the cloud.
Previous research frequently fails to take into
account the complex needs and legal limitations that the
healthcare sector faces, which results in security
solutions that might not be able to sufficiently safeguard
patient data that is sensitive or guarantee adherence to
laws like HIPAA and GDPR. Furthermore, even while
encryption methods like RSA are frequently used to
safeguard data, they are not the best choice as for as
cloud environments where performance and efficiency
are crucial due to their computational overhead and
scalability problems [27].
Moreover, not much study has been done on
combining steganography and sophisticated
cryptographic methods such efficient ECC to offer
multi-layered cloud security for medical data. Enhancing
data confidentiality, integrity, and obfuscation through
the combination of these strategies can reduce the
likelihood of tampering, illegal access, and data breaches
[28]. The creation of a thorough security architecture
that takes into account the particularities of healthcare
data, incorporates effective cryptography methods
designed for cloud systems, and guarantees regulatory
compliance is necessary to close this research gap.
Future research can greatly advance cloud security for
healthcare data and enable healthcare companies to use
cloud technology safely and efficiently by bridging this
gap [29].
3. Proposed System
The goal of the proposed system is to create a
multilayer security framework that is especially made to
safeguard medical data that is processed and stored in
cloud environments. The core of this strategy is the
combination of steganography and efficient ECC-AES
aims to leverage cloud computing's scale and flexibility
while addressing the particular security concerns
associated with healthcare data. Compared to
conventional encryption methods, efficient ECC-AES
provides strong encryption with reduced key sizes,
which makes it a good fit for cloud environments with
limited resources. The framework guarantees data
confidentiality and reduces the possibility of unwanted
access or data breaches by encrypting healthcare data
using ECC-AES. The framework uses steganography
techniques in addition to encryption to even more
obfuscate the existence of sensitive healthcare data.
Fig.1. Framework for Multilayer Approach for Securing
E-Healthcare Data
Cipher Text
Decrypted
using AES
Plain Text
Plain Text
Encrypted
using AES
Utilizing ECC to
reencrypt Ciphertext
& AES key
Cipher Text
Compress Cipher
Text using Brotli
Embed using 2D-
DWT Steganography
Cover
Image
Stego
Image
Extract using 2D-
DWT Steganography
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Strict key management procedures, strong
access restrictions, and assurances of compliance to
meet HIPAA and GDPR regulations are important
parts of the proposed system shown in Figure 1.
Maintaining the integrity and efficacy of the
security measures also requires regular personnel
training programs and security audits. The overall
goal of the research is to close the gap in the
literature by offering a complete security solution
that is especially designed to meet the special needs
of healthcare data in cloud environments. The
framework aims to provide better protection against
tampering, unauthorized access, and data breaches
by combining steganography and efficient ECC.
This will allow healthcare organizations to safely
utilize cloud technologies for increased productivity
and patient care.
Medical information poses the highest security
risk in the experience of the medical business.
Through the use of IOT devices hackers can use
botnets to obtain patient information shown in
Figure 2. For this reason, the safeguarding of IoMT
devices security and medical data is essential.
Modern communication techniques require the right
information to be sent at the right moment to the
right recipient. Patient records are safe and secured,
this is significantly more necessary for individually
identifiable medical information. A constantly
evolving threat landscape, driven by sophisticated
intrusion objectives, a growing number of security
vulnerabilities and unskilled and unaware
employees handling these private records often pose
a threat to the sharing and safe storage of medical
records. Healthcare records are typically
protected/concealed using conventional
cryptographic and steganographic methods, though
these methods often suffer from failure of prompt
executions.
Fig. 2. Multi-layer Model
3.1 Steganoraphy
To make the secret image more secure from hackers
and other attackers, it is incorporated within the cover
image. An RGB image of a natural scene serves as the
cover image. The YCbCr format is created from the
RGB colour-secured image using the equations
provided.
[Y Cb Cr ]= [0 128 128] + [0.298 0.588 0.115 -0.170
-0.332 0.499 0.499 -0.420 -0.082]. [R G B]
The hidden image will be embedded in the
luminance image plane (Y), leaving the other two
image planes (Cb and Cr) unchanged. Grayscale
medical imaging makes up the hidden image. Using the
thresholding approach, this hidden grayscale image is
transformed into a binary image. Depending on the
threshold value, the thresholding process turns the
pixels in the hidden images to either black or white. In
this study, global thresholding is utilized to produce a
binary image.
LSB approach is used to incorporate this binary
secret image into the cover image. The preferred
method for securing spatial domain images is LSB
steganography.
a) Brotli Technique
Brotli is a good compression algorithm for
handling data with numerous pattern and characters.
These identical characters are summarized into same
block. During the compression, this technique
divides the text data into small blocks. Each block is
then compressed separately and then encoding
algorithm is applied which is Huffman coding,
providing shorter codes to enhance the efficiency of
the compression process.
The decompression process involves the Brotli
decompression functions which includes Huffman
decoding, Output buffering and sliding window. The
Huffman decoding is used to restore the
representation of symbols into their original values.
The output buffering is used to store the
decompressed data, and then the sliding window is
used to track context during the decompression
process.
b) Discrete Wavelet Transform (DWT)
Proposed approach used a DWT with a mother
wavelet from HAAR. Applied 2D-DWT-2L on the
image's row (blocks), which was designed as a
sequential transformation process with the aid of
low pass and high pass filters. It should be
mentioned that level-2 coefficients were taken into
consideration for embedding in the proposed 2D-
DWT-2L idea. This was done primarily because
Presentation
layer
Application
Layer
Data Server
Cloud
Security
IoT
T
Self-
managemen
t
Backup
Cloud
BP
Senso
r
Wearabl
e Watch
Neck
Band
Wrist
Band
Network Layer
Access
Pointer
Access
Pointer
Route
r
Route
r
Internet
Patient
Hospita
l
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Volume 6, 2024
level-2 coefficients can offer a sizable local
characteristic set for text-embedding sans adversely
affecting the quality of the image.
Single-layer embedding can affect post-
embedding image quality and result in increased
visibility or perceptibility. Conversely, embedding
at a higher level coefficient may yield better results,
but at the expense of additional processing, which
may not be appropriate given the needs of modern
real-time applications. For this reason, we only used
a 2-level DWT coefficient for embedding in this
paper. The outcomes of this method are broken
down in relation to the image's columns. Figures 3 a
brief overview of this procedure.
The secret data T, which has already been
processed as cipher data is inserted using LSB
embedding to create stego image S. Even in the face
of cloud attack scenarios like RS-Analysis or
Steganalysis, our proposed solution aims to maintain
optimal pixel adjustment to maintain maximum
feasible imperceptibility, quality preserve, and
continuous transmission.
Our proposed approach splits the original source
image, also known as the cover-image, into several
8 × 8 blocks after processing it with HAAR-DWT.
A secured database is required in homoeopathic or
healthcare institutions to provide dependability and
security. Healthcare networks might experience
negative consequences like a denial of service due
to security and privacy issues. A single component
may be more severely impacted by some
vulnerability than by other.
Fig. 3. 2D-DWT-2L Decomposition process
3.2 Algorithm – Hybrid Model
Data encryption using a multilayer security
approach with ECC involves several steps to ensure
robust protection against unauthorized access and data
breaches. Here's an outline of the process:
Step 1: Key Generation
Choose a suitable elliptic curve and base point
G.
AES: Generate AES symmetric encryption key
KeyAES
ECC: Generate ECC key pair (private key: PrECC
public key: PuECC
Step 2: Encryption
AES Encryption
Encrypt M using AES with key KAES, resulting
in cipher text CAES.
ECC Encryption
Compute Secret key S=PuECC*G, where G is
the generator point on the elliptic curve.
Encrypt the Cipher text of CAES and AES Key
CECC=CAES*SAES
Step 3: Embed Encrypted Text into Cover Image
using Steganography
Compression:
The Cipher text data will be encoded using
Brotli Algorithm. Then converted from UTF-8
to base64, transferring the data into
hexadecimal format, finally the hexadecimal
converted into Binary.
The final output will be compressed text data
in binary form.
Embedding:
Compute 2D-wavelt transform of cover image.
It produces four bands such as: LL, LH, HL
and HH.
Select LL sub-band for embedding procedure,
this will be done using 2D-DWT technique.
Step 4: Extract the secret message from Stego
Image using reverse process:
Extraction procedure will be done using 2D-
DWT, the bits will be extracted and grouped
into binary form.
The outcome will be converted into
hexadecimal form and then decoded from
base64 to obtain the compressed text data
using Brotli.
Step 5: Decryption
ECC Decryption
Compute Secret Key S = PrECC*G
Compute CECC=C*S and AES Key
AES Decryption
Compute Message=CECC*KeyAES
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4. Performance Analysis
The proposed method used to look at an item is
called ex-ante evaluation; it involves looking at the
artefact before it is utilized and not evaluating it in a
real-world environment. This proposed system
approach assesses the artefact based on theoretical or
speculative scenarios. The operations and strategies
needed to successfully finish the processes of
decryption and encryption were made available to us
after installing these libraries data. Proposed model
needed text data to be saved as an image file so that the
AES and RSA algorithms could encrypt it.
0
2
4
6
8
10
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6
Image 7
Data
Analyser
Original
Image
Entropy
Entropy
(Post-
embedding)
Fig.6. Image Entrophy Analysis
0
10
20
30
40
50
Image 1
Image 2
Image 3
Image 4
Image 5
Image 6
Image 7
Data
Analyser
2D-DWT-2L
Existing
system
Fig. 7. Embedding Capacity Analysis
TABLE 1. COMPUTATIONAL COST EXISTING VS
PROPOSED
0
10
20
30
40
FMO LSB OMME Proposed
System
Computational Cost
(bits)
Methods
Fig. 5. Computational Cost between Existing and Proposed Method
Fig.6. Encryption Time
Fig. 7. Decryption Time
4. Conclusion & Future Work
By integrating various symmetric encryption and
steganography methods, the system offers several
security levels that improve secrecy and Efficiency.
Resource constrained cloud systems can benefit from
ECC because of its effective encryption skills, which
allow smaller key sizes to be generated sans sacrificing
protection. Following the creation of shareable hidden
keys and ephemeral keys, the encryption procedure
yields a symmetric key that is derived from a hash
function of cryptography. The E-Health data is
subsequently encrypted using this symmetric key,
guaranteeing privacy throughout storage.
Steganography provides another degree of obscurity by
Protocols
Computational Cost (bits)
FMO
16.410
LSB
31.8193
OMME
20.8795
Proposed System
11.97.33
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Volume 6, 2024
embedding the cipher text inside seemingly innocent
documents or images, thereby rendering it harder for
attackers to find or alter the information. The algorithm
offers a thorough approach to safeguarding E-Health
data in cloud environments, tackling the intricate
security issues that arise with healthcare data
governance.
In Future, checking the scalability of the proposed
model using different kinds of biomedical images with
other modalities. Introducing the various threats like
image rotation, resizing, tampering, etc., and evaluating
the performance analysis.
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problem to the final findings and solution.
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Conflict of Interest
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Engineering World
DOI:10.37394/232025.2024.6.13
Nagamany Abirami, M. S. Anbarasi
E-ISSN: 2692-5079
135
Volume 6, 2024