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May - June 2020
ISSN: 0193-4120 Page No. 4232-4238
4232
Published by: The Mattingley Publishing Co., Inc.
An Efficient Encryption and Decryption
Method for Image Steganography
1Ranjitha R, 2Mallikarjun Shastry PM
1PG Student, School of C and IT, Reva University, Bangalore, India
2Professor, School of C and IT, Reva University, Bangalore, India
1ranjitharanju836@gmail.com, 2mallikarjunshastry@reva.edu.in
Article Info
Volume 83
Page Number: 4232-4238
Publication Issue:
May - June 2020
Article History
Article Received:19 November 2019
Revised: 27 January 2020
Accepted: 24 February 2020
Publication: 12 May 2020
Abstract
In a digital world, data protection has become highly important issues. For
secure data transmission, steganography and cryptography are used where
steganography is focusing on the existence of a message secret and
cryptography is focusing on content message secret combing both
technologies will give more protection for data. In this paper, a base64
encoding method is used to encrypt the secret information which will be
embedded into the cover image. An android application is built to perform
encoding and decoding operations which is user friendly, fast and secure.
Image quality is measured using Peak Signal to Noise Ratio (PSNR), Mean
Square Error (MSE) and histogram analysis. The experimental result shows
that the stego image can store large amount of data while PSNR, MSR, and
histogram analysis values proves that stego image quality is almost similar
to cover image and distortionless images.
Keywords: Steganography, LSB, cryptography, Base64.
1. Introduction
In the current era of digital world, secure data
transmission becomes a more challenging task.
Cryptography is a technique to protect the security of the
information and this makes use of encryption and
decryption processes to keep the message secrete which
means Secret writing. However unauthorized can access
the information by changing the information to be
transmitted to overcome this problem steganography is
used [1]. Steganography is derived from the Greek word
steganos which means “Covered” and graphy means
“Writing”, i.e. covered writing [12]. The basic idea
behind steganography is hiding the secret data in some
objects. Steganography uses different types of objects to
hide the data like image, audio, and video. The most
popular one is image steganography because of their
frequency on the internet [2]. Image steganography
techniques work on two different domains like space
domain also known as pixel domain where steganography
operation directly performed on the pixel and transform
domain, where message embedding is performed in the
transformed image [3]. The object which is used to cover
the secret information is called cover image on the based
compression of image cover image is divided into lossy
and lossless compression. Lossy compression is more
popular on the website because of Very small file sizes
and lots of tools, plugins, and software support it but once
the image is compressed it can’t get back to the original
image which results in data loss on each compression
image will lose its original picture quality. With 50%
compression applied image file size decreased by 90%.
With 80% compression applied image file size decreased
by 95%. [4] e.g. like JPEG image. In lossless
compression, the compressed image will never lose their
data and slightly decreased in image file size it maintains
the same picture quality of the original image. E.g. BMP,
GIF, andPNG. JPEG spatial image data transforms into
the frequency domain and subjected to lossy
compression, on each compression process image loses
its data and introduced too much noise in it. When image
is converted back to the spatial domain it will be very
hard to detect the error using error correction coding.
Hence, it was concluded that steganography would not be
possible in JPEG images. [5].The algorithms which are
used to overcome this problem is very complicated.
Whereas for a PNG and BMP image a simple LSB is
applicable without any loss of data on compression. Also,
they both fair almost equal in terms of storing capacity
and image quality of the final image. Lossy compressed
images are complicated for steganography processes it
needs extra compression algorithm to maintain the
integrity of the data where lossless image are well
suitable for steganography processes. Steganography and
cryptography are two different processes where
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steganography is focused on keeping the existence of a
message secret and cryptography focuses on keeping the
content message secret [12]. Combination of both
methods gives strong steganography algorithm.
In the rest of this paper is organized as follows:
Section 2 gives a brief overview of related work and
drawbacks of the existing system. Section 3 gives a
detailed description of the proposed system. Section 4
implementation of the proposed system. Section 5 results
and discussion. Finally, the conclusion is given in section
6.
2. Related Work
A text steganography method in the JPEG image was
studied and proposed a system by Abbas Darbani et al.
[3]. Here JPEG images are used for steganography
because of the smaller size which is suitable for
transmission and Least Significate Bit method is used for
steganography. Since part of the data will be lost because
of the lossless compression nature of the image proposed
system where a message is embedded after the
discretization stage and two adjust pixel is used and
embedding processes are depended on replacement table
which will be a major issue. JPEG images are not well
suitable for steganography processes.
A new approach of hiding data in BMP image using
Caesar Vigenere Cipher Cryptography an experiment is
carried out by I Gede Arya Putra Dewangga et al. [6]. In
this study,cryptography is used to hide the secret message
which is inspired by the Vigenere cipher technique and
then the message is inserted into the LSBs to hide one
byte of a secret message it uses the eight-byte of the
cover image without compromising the file quality.
PSNR and MSR values are calculated to measure in cover
and stego image qualities.
A survey on LSB steganography between the BMP
and JPEG isdone by Eltyeb E. Abed Elgaba [7].
A Comparison study is done on lossless compressed
images (e.g. BMP, PNG, and GIF) and lossy compressed
images (e.g. JPEG) for LSB steganography. Strengths and
weaknesses have been observed. BMP image can hide a
large amount of data and image distortion will not occur
and JPEG image uses less space but robustness against
image manipulation and resistance to statistical attacks is
low and increases the amount of data distortion also
increases.
Compared to two digital image file formats using
different compression techniques is done by Bharat Sinha
[8]. Images are two types of file format one is lossless
compression techniquedata will not lose after
transmission and lossy compressed technique data will
lose after transmission comparison study is done between
the PNG and JPEG where PNG image will more suitable
for LSB steganography both BMP and PNG images have
similar characteristics.
A survey is done on a stenographic tool for the BMP
image format by Prof.SumedhaSirsikar et al. [9]. Various
tools performances are evaluated by PSNR for stego and
cover images values are very less and tools are provided
by GUI and command line which is very complicated to
use.
Image steganography based on the RSA algorithm is
implemented by Rituparna Halder et al. [10].
Steganography is combined with RSA cryptography
algorithm to provide more security to data along with
encryption and decryption add authentication module for
extra security from all above prevision studies in this
study would be used steganography with more efficient
and easy cryptography method i.e. Base64 and LSB
steganography used for PNG image format which is
distortionless, maintain data integrity and store more data.
An android application is built which user friendly and
also used for private communication.
JPEG images are not well suitable for LSB
steganography because data loss occurs.
The compression algorithm which is used to maintain
data integrity is complicated to implement.
Steganography alone has less security.
3. Proposed Encryption and Decryption
The purpose of the proposed system is to provide an
efficient and easy way to transfer secret data over the
communication channel by using the combination of
steganography and cryptography methods where the
encryption method gives extra security level to get the
original data.
The proposed system has the following objective.
Stego image is.PNG image format which maintains
data integrity.
More security on data.
Provides user-friendly application.
Maintains good image quality.
A. Overall Design Ideas.
As shown in fig.1 is the overall design idea of the
proposed system where steganography is combined with
cryptography to add more security for the system.
Steganography using Least Significate Bit (LSB) method
to hide secret data in the image cryptography using the
Base64 encryption method to encrypt the secret data.
The proposed system has two phases encryption
phase and decryption phase. In the encryption phase,
secret data will hide in the image before embedding data
in.
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Figure 1: Architectureof steganography processes.
Image data will get encrypted into cipher text. In the
decrypted phase, first data is extracted from the image
then ciphertext is converted into plain text. An image that
is used to hide the data is called a cover object. An image
which embedded with data is called stego object.
B. Encryption and Embedding method.
As shown in fig.2, it is an encryption and embedding
phase in this phase secret data which is in the form of
plain text get encrypted by the Base64 method first, secret
information is converted into ASCII code then ASCII
code is again converted into binary data and binary data
converted into ciphertext. Now ciphertext is embedded
into the cover object. Cover object can be any type of
image (e.g. JPEG, PNG, BMP) using LSB steganography
processes to form a stego object where stego image is.png
image format so when attackers are trying to compress
the stego object image will not get compressed and it
maintains the data integrity.
Figure 2: Encryption and Embedding phase.
C. Extraction and Decryption method
Fig.3 shows an extraction and decryption phase in this
phase, the first information is extracted from the stego
image extracted information is decrypted to get back the
original image.
Figure 3: Extraction and Decryption phase.
4. Implementation of Proposed Method
Image compression is a technique that is widely used in
steganography. It is mainly classified into two types
lossless compression and lossy compression wherein
lossy compressed image (e.g., JPEG image format) will
not retain its original data when it undergoes some
transmission. When attackers try to extract the
information from the image it loses some important data
whereas in lossless compression image it preserves its
original data correctly hence lossless compression is
chosen for LSB steganography (e.g., BMP, PNG, and
GIF image format).
In the proposed method steganography is combined
with cryptography to provide more security for secret
information. This technique makes sure that a secret
message is encrypted before hiding in the cover image so
when hackers got the data from the cover image still they
can’t access the encrypted data this provides the extra
layer of security and this is done by using an efficient
encryption and decryption algorithm. The proposed
system uses two main technologies for secure data
transmission are steganography which embeds the
sensitive data in an image by using most popular
technique called Least Significate Bit(LSB) and
cryptography which changes the meaning of message
called cipher and method which is used to encrypt the
data is the proposed system is a base64.
To transmit the secret data from the sender to
receivers in such a way that intruder does not suspect the
existence of the information an effective system is
designed. System design is divided into two parts namely
Embedding function and Extraction processes. In
embedding function secret message encryption using
base64 and then hides the encrypted data in the cover
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image using the LSB technique is taking place. It makes
sure that encrypted data is embedded in the cover image
to form a stego object. In the second part of the system,
Extraction is taking place where ciphertext is extracted
from the stego object using the LSB technique and
ciphertext is decrypted to get back the secret data in the
reverse order of base64 method.
A. Least Significate Bit (LSB):
Steganography is a process of hiding the secrete message
with a cover image the method which is used for
embedding the information within a cover image is the
least significate bit (LSB) which is simple and popularly
used approaches. In this method, the least significant bits
of some or all of the bytes inside an image is replaced
with a bit of the secret message. Every digital image is a
finite set of pixels each pixel is the colour combination of
RGB modal i.e. 24bit image file one can store 3 bits in
each pixel by replacing it by secret message bits. Suppose
for example if we want to hide a message “A” is a cover
image convert message “A” to ASCII code i.e.1000001
here we are using 3 pixels that are about 9 bytes for
insertion to replace all the least significate bits. Now
replace the last bits of the pixel with ASCII code of “A”
bits as shown below [14]. Fig.4 shows the status before
insertion of pixel and Fig.5 shows the status after the
insertion of pixel.
10000000
10100100
10110101
10110101
11110011
10110111
11100111
10110011
00110011
Figure 4: before insertion of pixel
10000001
10100100
10110100
10110100
11110010
10110110
11100110
11000011
00110011
Figure 5: After insertion of the pixel
As discussed in the related work section lose less
compression image like.PNG image format is the best
image steganography because when an image tried to
compressed image will not lose its data.
B. Base64 Encoding method.
Base64 is one of the most popularly used encoding
algorithm to transmit over the internet of 8-bit bytes code
which belongs to binary-to-text encoding schemes. Text
is converted into ASCII code of string format and
translated into radix-64 represented. Its advantages are
that the efficiency of the algorithm is high, the coded
results are short, also unreadable[20].
C. Algorithm of the proposed system:
Algorithm to hide data into image:
Algorithm Hiding:
Input: CoverImage, SecreteMessage, SecreteKey
Output: StegoImage
Read the CoverImage, SecreteMessage, and SecreteKey
Ciphertext = Compress (SecreteKey, SecreteMessage)
FindLSBs (CoverImage)
While (CoverImage):
StegoImage = Embbed (Ciphertext into CoverImage)
Return StegoImage
Algorithm to Unhide data from image:
Algorithm Unhiding:
Input: StegoImage, SecreteKey
Output: CoverImage, SecreteMessage
Read the StegoImage, and SecreteKey
If (SecreteKey == StegoImage(SecreteKey))
FindLSBs (StegoImage)
While (StegoImage):
CoverImage, SecreteMessage = Uncompressing
(StegoImage)
Return CoverImage, SecreteMessage
5. Result and Discussion
Anandroid application is designed to perform image
steganography processes. Select the cover image of any
format, enter the secret data next give a secret key for
authentication purposes. First secret data will be
converted into ciphertext using the Base64 encoding
method then encoded text embedded into the cover
image. Encoded images will get saved in the device
in.png format to overcome the problem of data loss. Now
in the decode phase select the image and enter the same
secret key to access the secret data if the secret key is the
wrong application gives a message wrong key if key is
correct secret data will be displayed.
The result of the proposing system is evaluated using
three parameters Peak Signal to Noise Ratio, Mean
Square Error (MSE) and Histogram.
Compression table of PNG (portable network
graphics)and JPEG (joint photographic expert group)
images are done in the table 1.
Table 1. Property Comparison of PNG and JPEG.
Property
LSB in
PNG
LSB in
JPEG
Visibility
Low
Low
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Independent of File
Format
Low
Low
Robustness Against
Statistical Attack
Low
Medium
Stego analysis Detection
Low
Medium
Payload Capacity
High
Medium
Data Capacity
High
Low
Efficient When Amount
of Data
Reasonable
High
Medium
Robustness Against
Image Manipulation
Low
Medium
Percentage Distortion
Less Resultant Image
High
Medium
Comparison of LSB for lossless and lossy images is
one in the above table which tells that PNG image format
is well suitable for LSB steganography processes where it
stores large amounts of data with high payload capacity,
less distortion in the resulted image and low stego
analysis detection when compared to JPEG image. Due to
the loose less compassion nature of the JPEG image, it
does not maintain data integrity. When it undergoes some
compression data loss occurs to overcome this problem
entropy encoding is used to produce stego image which is
a very complicated compression method to maintain the
data integrity. Table 2 shows the comparison of the
results obtained by the proposed method with PSNR and
MSE [6]
Table 2: Comparison of Results
.
Sr.
No
Cover
Image(.Jpeg)
Proposed
system
Existing
system
PSNR
MSE
PSN
R
MSE
1
nature
75.56
0.0018
59.85
0.0677
2
animal
73.54
0.0028
60.25
0.0617
3
flower
79.85
0.0006
7
60.63
0.0567
4
smiley
91.62
4.47
63.34
0.0303
5
peacock
86.2
0.0015
62.21
0.0394
The image quality of an image is measured using
peak signal to noise ratio (PSNR) and mean square error
(MSR)[15] for stego image and cover image and also
histogram is used to measure the distortion of stego
image and cover image using the following equations.
PSNR =
MSR=
Mean square value is calculated for the original
image and compressed image lesser the value less error in
the image, which is an inverse relation between MSE and
PSNR which means a higher value of PSNR is good
because it means that the ratio of signal to noise is
higher[16]. MSR and PSNR values of the stego image
and cover image of an image and intensity of the images
is shown in Table 3.
Table 3: Histograms of encoded and decode images
Sl. No
Cover image
Stego image
1
nature
nature
2
animal
animal
3
flower
flower
4
smiley
smiley
5
peacock
peacock
Five image samples of different size are taken for
experiments and image quality measurement is done on
those images PSNR and MSR is calculated and we got a
result with higher PSNR value and low MSE value which
proves that there is no much difference between the cover
image and stego image and image is maintaining the
actual quality. Histogram is used to measure the
distortions less of the cover image and stego image [14].
PSNR and MSR values are compared to the existing
system and the proposed system fig.6 shows that the
proposed system has the highest PSNR value than the
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existing system and fig. 7 shows that the proposed system
has less error value than the existing system.
Figure 6: PSNR comparison.
Figure 7: MSE comparison.
6. Conclusion
In this study, steganography is combined with the Base64
encoding and decoding method for data security
purposes. An android application is built which isa fast,
secure and user-friendly interface to encode and decode
images.To evaluate the performances of the proposed
system PSNR and MSR, parameters are calculated. The
result shows that the proposed system can store more
amount of secret data while a stego image is most similar
to the cover image. Histogram graphs show that
distortions less between the cover image and stego image.
Comparison graphs are drawn to show a proposed system
PSNR and MSE values are improved by 33% and 43%
respectively than the existing system. This proposed
system is implemented to increase the security of the data
when transmitted through a highly vulnerable and insure
network.
Acknowledgment
This is a matter of pleasure for me to acknowledge my
gratitude to the School of Computing and Information
Technology, Reva University for allowing me to explore
my abilities via this paperwork. I would like to express
my sincere gratitude to our project guide,
Dr.MallikarjunShastry PM, for his valuable guidance and
advice in completing this paperwork. Let me take this
opportunity to thank the School Director, Dr.SunilKumar
S. Manvi for the wholehearted support extended to me
throughout the conduct of the study. Last but not the
least, I would like to express my sincere thanks to my
family members, friends for their immense support and
best wishes throughout the curriculum duration and the
preparation of this paper.
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