Pixel Value Difference Based Image Steganography
with One Time Pad Encryption
Giridhar Maji
Sharmistha Mandal
Department of Electrical Engineering
Asansol Polytechnic, Asansol, India
Giridhar.Maji@gmail.com
Department of Computer Science and Technology
Kanyapur Polytechnic, Asansol, India
sharmistha.cse@gmail.com
Narayan C. Debnath
Soumya Sen
School of Computing and Information Technology
Eastern International University, Vietnam
narayan.debnath@eiu.edu.vn
A. K. Choudhury School of Information Technology
University of Calcutta, Kolkata, India
iamsoumyasen@gmail.com
Abstract—Pixel value differencing (PVD) and Least Significant
Bit (LSB) embedding are well known spatial domain steganographic techniques. PVD utilizes the sharp changes of intensities
among adjacent pixels where a large number of secret bits
could be embedded without any perceptible change. one-time
pad (OTP) symmetric cryptography is known for its security.
In the proposed scheme one or more LSB bits of the selected
pixels are used depending on the pixel intensity difference with
neighboring pixels in 2 × 2 image blocks of the cover image.
Secret bits are encrypted using OTP with randomly generated
pre-shared key. Such encrypted bits are completely random and
resemble noise hence make the scheme robust against different
statistical attacks. Comparative simulations with some wellknown PVD-based techniques show good results in terms of
visual imperceptibility and different quality metrics such as MSE,
PSNR, SSIM etc.
Index Terms—Image Steganography, Pixel value difference(PVD), Least Significant Bit(LSB), One Time Pad
(OTP),Spatial domain
I. I NTRODUCTION
The Internet has become the most popular medium of
digital communication but with a greater threat to privacy
and secrecy. All messages travel through the public channels
from sender to receiver and subject to monitoring as well as
moderation. Two different well-known approaches to solve
the problem are known as cryptography and steganography.
In cryptography, the secret messages are encrypted to some
illegible gibberish (known as ciphertext) with the help of
some random keys before sending them through the public
channel. Upon receiving the ciphertext receiver uses the key
to decrypt the original message back. The secrecy of the
message is kept by the keys without which an interceptor
could not understand the message but knows the fact that
some hidden communication is taking place. In the case of
steganography, the goal is not only to hide the secret but
also to make the existence of the communication hidden. As
a result, when cryptography attracts hackers, steganography
remains undetected to others except for the intended receiver.
Steganography uses a cover media to hide some (often encrypted) secret message by embedding them in the redundant
noise portion of the cover to make it imperceptible. Cover
media can be an image, video or audio. When an image is
used as a cover then it is called image steganography. Based
on the way secret message bits are embedded image steganography is mainly categorized into transformed (or frequency)
domain techniques and spatial domain techniques [1]. Some
of the popular frequency domain techniques are discrete cosine
transform (DCT) [2], discrete wavelet transform (DWT) [3],
discrete Tchebichef transform (DTT) [4] etc. Least significant
bit (LSB) substitution is the most common technique in spatial
domain where image pixel intensity values 8th bit is used
to embed the secret message bits. Many different variations
of this technique exist. Some used more than one bit [5] to
embed, others have used some kind of transformation (e.g.
Arnold transformation) of the secret bits before embedding [6],
some researchers have used the RC4 algorithm to randomize
the secret bits instead of storing them sequentially while
embedding in pixel LSBs [7], some even first encrypts the
secret message [8], [9] and then embeds. Authors in [10] used
a reference image along with the cover image for encoding of
the secret bits before embedding into the cover image LSBs.
Edge areas in an image have large variations in adjacent pixel
intensities and this fact has been exploited to hide many secret
message bits into those pixels without any perceptible changes
[11], [12].
Pixel value differencing (PVD) method was first proposed
by Wu and Tsai [13] where the cover image is first divided into
two-pixel blocks. These blocks are non-overlapping in space.
Blockwise pixel intensity value difference is used to hide
secret bits. More the difference more bits it can hide. Later a
large number of methods with modified PVD and LSB technique have been proposed [14]–[18]. A comprehensive survey
of different PVD based image steganography techniques is
available in [19].
The Vernam cipher [20] (also known as one-time pad, OTP)
is a symmetric key cipher i.e. same key is used for encryption
as well as for decryption of the original message. It is defined
over the alphabet {0 1}. If the secret binary string is m and
a random binary key string of the same length is k then
encrypted secret binary bits (cipher bits) c = m exclusive OR
k (c = m ⊕ k) Again, to get back the original secret message
receiver has to again apply the same XOR operation on the
encrypted cipher string with the key. m = c ⊕ k; The key
k is generated each time randomly. OTP is used block-wise
to encrypt the secret bits. Researchers in [2], [3] have used
OTP based encryption of secret bits before embedding them
into frequency domain coefficients. If a truly random key is
used and key length is same as message length then OTP is
said to be the strongest encryption and very difficult to break,
highly resistant to brute force attacks as it requires the attacker
to try all possible combination of keys [21]. In our proposed
method we shall employ OTP based encryption of the secret
text with randomly generated keys and then embed them using
a modified PVD method by partitioning the cover image into
2 × 2 pixel blocks.
Rest of the paper is organized as follows. Different related
studies are done in section II. Proposed scheme is explained in
section III with an illustrative example. Experimental results
are discussed in section IV. Finally, section V concludes the
study.
II. R ELATED W ORK
One Time Pad (OTP) encryption technique was first proposed by G. Vernam in 1917 and is very popular in the
cryptography domain. Very recently cryptographic techniques
have been used along with steganographic methods for achieving dual-layer security. OTP has been used along with many
different types of steganographic techniques to make the
scheme more robust and secure. Researchers in [8] used OTP
based encryption along with LSB steganography where they
have used alphanumeric messages of size 8 byte to 128 byte
for embedding in a color cover image. They first used OTP to
encrypt the text message bits and then used 3 LSB bits of the
cover image to insert the encrypted bits. Stego image quality is
measured by mean square error (MSE) and peak noise to signal
ratio (PSNR). Authors in [2] used OTP along with DCT where
they have encrypted the message using a random key with the
Vernom cipher and then embed them into the cover image dct
coefficients with a block size of 16 × 16. Normalized cross
correlation (NCC) metric is used along with MSE and PSNR
for quality evaluation. OTP is used with DWT in [3] where
secret message is a 32*32 binary image which is embedded
into the LL4 and the HH4 subband of a 512 × 512 cover
image into wavelet transformed domain after encoding using
randomly generated keys. MSE, PSNR, and NCC are used
as a quality metric. Pixel value differencing (PVD) method
is first introduced in [13] by Wu and Tsai. It utilizes the
difference between two consecutive pixel values and uses it to
embed secret bits. But this method is prone to histogram-based
attacks and to overcome a modified PVD method is proposed
in [22]. Wu et al in [16] proposed a combined method
using 2-pixel block PVD and 3 bit LSB for higher security
and lower distortion. Authors in [17] developed a modified
LSB embedding with 4-pixel blocks with PVD. G. Swain in
[23] proposes two adaptive PVD methods with 2 × 2 nonoverlapping blocks that give good hiding capacity and with
3 × 3 overlapping pixel blocks that give good PSNR metric.
In the first technique, both horizontal and vertical edges were
considered whereas in the second method any one of them is
considered. We have observed from literature survey that OTP
gives good security with the less computational burden and
randomizes secret text bits quite well with randomly generated
keys. Again, a suitably modified PVD method provides higher
capacity in terms of the amount of secret data embedded. But
PVD with higher capacity is prone to RS attack as well as
histogram pair steganalysis. So we have skipped using rangebased approach to embed a higher number of bits into the
high-intensity pixels. Rather we use only selected pixels to
avoid the above steganalysis attacks with a little compromise
with capacity. We shall embed 2 bits on selected 4-bit image
blocks. Hence it becomes our natural choice to combine OTP
and modified PVD for a fast, secure, robust but lower capacity
steganography scheme.
III. P ROPOSED S CHEME
The proposed scheme using One Time Pad (OTP) and
modified Pixel Value Differencing (PVD) is outlined in fig. 1.
It utilizes the benefits of both the techniques where OTP
enhances the security by randomizing the secret bits and PVD
ensures higher capacity by utilizing the best possible pixels to
embed the secret bits. Our proposed scheme first converts the
secret message characters into 8 bit ASCII equivalent binary
string. Next 4 bit groups are formed and converted to decimal.
Cover image is also divided into 2×2 blocks as shown in fig.2.
Each pixel is marked as p1 to p4. It gives a total of six different
pixel pairs with pixel value differences as shown in table I.
Secret Text Message
Random Generated
Key for OTP Based
Encryption
Secret Binary String
Secret Text Message
Secret Binary String
Encrypted Binary String
Encrypted Binary String
4 bit groups made &
converted to decimal
Decimal value converted
to 4 bit binary equivalent
Cover Image
Embedded into Cover
Image 2×2 Blocks
using PVD to create
Stego Image
Stego Image
Decimal value Extracted
from Stego Image 2×2
Blocks using PVD
Public channel (Internet)
Sender Side
Recipient Side
Fig. 1: Block Diagram of the Proposed Scheme.
Every character of the secret message is converted to 8bit binary and it is then encrypted by XORing with 8 bit
P1
P2
P4
P3
Fig. 2: Pixels of a 2 × 2 cover image block.
TABLE I: Possible pixel pairs with value differences
Sl. No.
1
2
3
4
5
6
Pixel Pair
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
Difference
d12 = d21 = |p1 − p2|
d13 = d31 = |p1 − p3|
d14 = d41 = |p1 − p4|
d23 = d32 = |p2 − p3|
d24 = d42 = |p2 − p4|
d34 = d43 = |p3 − p4|
Sorted Difference
dmax1
dmax2
dmax3
dmax4
dmax5
dmax6
randomly generated keys. Thus 8-bit of the encrypted secret
is created. These 8 bits will now be embedded into two
consecutive 2×2 cover image blocks with modified pixel value
differencing technique. Each cover image block will be used
to embed 4 bits of encrypted text. So, 8 bits of encrypted text
is divided into two 4-bit groups and each of them converted
to an unsigned integer. The range of value will be 0 15 in
decimal (0000 - 1111). Our aim is to now embed this number
into the 2×2 pixel block in such a way that it can be recovered
in the receiver side without any loss of information.
A. Embedding Algorithm using PVD
Secret message is converted to 8-bit ASCII and cover image
divided into 2 × 2 pixel image blocks before embedding. An
8-bit random key(K) is also generated and used for OTP
encryption to scramble the secret bits and make the system
more secure. The same 8-bit key is used to encrypt all the
secret message and communicated to the receiver separately.
Complete embedding process is depicted in Algorithm 1.
Please note the value must be chosen in such a way so that
even after the embedding of the secret bits, dmax1 remains on
top of the sorted list. It can be observed that at a maximum,
pixel intensity of the highest-intensity pixel may be reduced
by 4 due to changing the 3rd LSB from 1 to 0. Hence the value must be more than 4 to be able to extract the message
successfully. A complete example is shown in section III-C
with step by step calculations to embed a string (’hi’) in a
sample cover image.
B. Extraction Steps
Extracting the secret from the stego image becomes easy
when the pre-shared 8-bit key(K) is available with the receiver.
Receiver has to follow the similar process of dividing the stego
image into 2 × 2 blocks and then do the per block processing
as detailed in algorithm 2 to recover the secret text.
C. An Illustrative Example
Lets say the secret text is Hi. In ASCII it is 72 105. In
binary, it is 0100 1000 0110 1001. Now consider six 2 × 2
cover image pixel blocks as shown in figure 3 taken from gray
Algorithm 1: Data Embedding
input
: Secret text message(M ), Random Generated
OTP key(K), Cover Image
output
: Stego Image
Step 1: Convert the secret text characters each into an
8-bit binary string.
Step 2: Each character is encrypted using 8-bit random
generated key using OTP as: Ci = Mi ⊕ K, where Ci is
the encrypted bits and Mi is the message bits, K being
the OTP key. Where i denotes the characters in the secret
message.
Step 3: 8-bit encrypted string is divided into two 4-bit
nibbles (N).
Step 4: Cover image is divided into 2 × 2 pixel blocks
and every 4 bits are embedded into two consecutive
image blocks.
Step 5: Find all possible pixel value differences (d1 to
d6 ) and sort in decreasing order so that maximum value
appears in the top (= dmax1 = |pi − pj |).
Let dmax1 is the difference between pixels pi and pj .
Similarly, dmax2 is the second top element in the list.
if (dmax1 == dmax2 ) then
Skip the block and continue.
else if (dmax1 − dmax2 > ) then
if (pi > pj ) then
Substitute 2 LSB bits of pi with first 2 bits of N
Substitute 2 LSB bits of pj with last 2 bits of N
Set 3rd LSB bit of Pi to 1 to indicate that the
current block contains hidden data bits.
else
Substitute 2 LSB bits of pi with last 2 bits of N
Substitute 2 LSB bits of pj with first 2 bits of N
Set 3rd LSB bit of Pj to 1 to indicate that this
block contains hidden data bits.
else
Set 3rd LSB bit of M AX(Pi , Pj ) to 0. //Indicates to
skip the block
converted image fabric.png provided with Matlab. The blocks
are marked as b1, b2 . . . b6. Now we embed 4 bits in each
such block. For each block, pixels are marked as p1 , p2 , p3
and p4 . For b1 the pixel values are p1 = 49, p2 = 68, p3 =
54 and p4 = 44. Now as shown in Table II we calculate
all possible pixel value differences and sort them to obtain
dmax1 > dmax2 > · · · > dmax6 . Then we select the highest
difference. And store 2 bit of secret into the pixels that gives
maximum difference. In this case for b1 it is p2 and p4 . Now
p2 > p4 , so first 2 bit of the secret (01) is stored into the
LSBs of p2 and it’s value changes to 69 from 68. Similarly
after embeddeing last 2 bit of secret(00) into LSBs of p4 it’s
value becomes 44 (no change). Now indicator bit (3rd LSB of
p2 ) is set to 1 (to indicate that this block contains payload) and
p2 value remains 69. In a similar way b2 and b3 hides data
but in case of b4 the difference between dmax1 and dmax2
Algorithm 2: Data Extraction
input
: Stego Image, Pre-shared OTP key(K)
output
: Hidden text message (C)
Step1: Divide the stego image into 2 × 2 blocks with
pixels p1 , p2 , p3 and p4
Step2: Calculate all pixel difference values block-wise.
Step3: Sort the pixel difference value in decreasing order
to obtain dmax1 > dmax2 · · · > dmax6 . Where dmax1
is the highest pixel difference.
Let dmax1 = |pi − pj |
Step 4:
if (dmax1 == dmax2 ) then
Skip the block and Continue.
else if (3rd LSB of M AX(Pi , Pj ) is 0) then
Skip that block
else if (3rd LSB ofM AX(Pi , Pj ) is 1) then
/* Extract the hidden data bits from Pi and Pj */
Extract first two bits of secret data from
M AX(Pi , Pj )s 2 LSBs;
Extract last two bits of secret data from
M IN (Pi , Pj )s 2 LSBs;
Combine first and last 2 bits to obtain 4-bit data.
Step 5: Repeat Step 4 to collect 4-bit data from the next
image block and append to create 8-bit secret data (C)
which is actually the OTP encrypted data
Step 6: Use 8 bit OTP key (K) with C to obtain the
hidden binary as M = C ⊕ K
Step 7: Convert 8-bit binary into ASCII character to get
the hidden text message.
is less than the threshold ( = 5) so we skip the block and
continue to b5. Our 16 bit secret embedding completes within
5 blocks. Hence 6th block is unused.
49
68
94
117
114
81
64
61
75
106
123
109
44
54
74
103
102
91
65
59
82
116
119
93
b1
b2
b3
b4
b5
(a) Baboon Original
(b) Baboon Stego
(c) Boat Original
(d) Boat Stego
(e) Lenna Original
(f) Lenna Stego
Fig. 4: Visual comparison between (a) Original Image
and (b) Stego Image.
original
embedded
500
500
0
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
b6
49
69
94
118
117
82
64
61
77
106
123
109
44
54
72
103
112
91
69
59
82
118
119
93
1000
500
500
0
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fig. 3: Selected cover image blocks: original (above) and after
embedding (below).
All test images are taken from SIPI image database
(http://sipi.usc.edu/database/database.php?volume=misc). We
have resized them to 256 pixel × 256 pixel and converted to
8-bit grayscale before processing. Secret text has been taken
from arbitrary web pages. As OTP key is randomly generated
so, on every run hiding capacity and image quality metrics
will vary. We have used same image to hide same secret
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
500
500
IV. R ESULTS AND D ISCUSSION
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
1000
0
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Fig. 5: Histograms of selected cover image and stego
image: Baboon (top), Boat and Lenna(bottom)
TABLE II: Illustrative calculation steps to embed Hi using the proposed scheme
Block # Pixel Pair
b1
b2
b3
b4
b5
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
p1p2
p1p3
p1p4
p2p3
p2p4
p3p4
Pixel Differences
Sorted differences
d12 = d21 = |p1 − p2 | = 19
d13 = d31 = |p1 − p3 | = 5
d14 = d41 = |p1 − p4 | = 5
d23 = d32 = |p2 − p3 | = 14
d24 = d42 = |p2 − p4 | = 24
d34 = d43 = |p3 − p4 | = 10
d12 = d21 = |p1 − p2 | = 23
d13 = d31 = |p1 − p3 | = 9
d14 = d41 = |p1 − p4 | = 20
d23 = d32 = |p2 − p3 | = 14
d24 = d42 = |p2 − p4 | = 43
d34 = d43 = |p3 − p4 | = 29
d12 = d21 = |p1 − p2| = 33
d13 = d31 = |p1 − p3 | = 23
d24 = d42 = |p2 − p4 | = 21
d14 = d41 = |p1 − p4 | = 12
d34 = d43 = |p3 − p4 | = 11
d23 = d32 = |p2 − p3 | = 10
d12 = d21 = |p1 − p2 | = 3
d13 = d31 = |p1 − p3 | = 5
d14 = d41 = |p1 − p4 | = 1
d23 = d32 = |p2 − p3 | = 2
d24 = d42 = |p2 − p4 | = 4
d34 = d43 = |p3 − p4 | = 6
d12 = d21 = |p1 − p2 | = 31
d13 = d31 = |p1 − p3 | = 41
d14 = d41 = |p1 − p4 | = 7
d23 = d32 = |p2 − p3 | = 10
d24 = d42 = |p2 − p4 | = 24
d34 = d43 = |p3 − p4 | = 34
dmax1 = d24 = 24
dmax2 = d21 = 19
dmax3 = d23 = 14
dmax4 = d34 = 10
dmax5 = d31 = 5
dmax6 = d14 = 5
dmax1 = d24 = 43
dmax2 = d34 = 29
dmax3 = d21 = 23
dmax4 = d34 = 20
dmax5 = d23 = 14
dmax6 = d31 = 9
dmax1 = d12 = 33
dmax2 = d13 = 23
dmax3 = d24 = 21
dmax4 = d14 = 12
dmax5 = d34 = 11
dmax6 = d23 = 10
dmax1 = d43 = 6
dmax2 = d13 = 5
dmax3 = d42 = 4
dmax4 = d12 = 3
dmax5 = d23 = 2
dmax6 = d41 = 1
dmax1 = d13 = 41
dmax2 = d34 = 34
dmax3 = d12 = 31
dmax4 = d24 = 24
dmax5 = d23 = 10
dmax6 = d14 = 7
Selected Pixel Pair
p2p4; 01 is substituted in last 2 LSB of p2 and
00 in p4 . p2 =68=0100 0100
updated p2 = 0100 0101 =69
updated p4 = 0010 1100 =44
With indicator 3rd LSB set,
p2 = 0100 0101 =69
p2p4; 10 is substituted into last 2 LSB of p2 and
00 into p4 . p2 =117=0111 0101 updated p2 =
0111 0010 =114 updated p4 =0100 1000 =72
With indicator 3rd LSB set, P2 = 0111 0110 =
118
p1p2; 01 is substituted in last 2 LSB of p1 and
10 in p2 . p1 =114=0111 0010 updated p1 =
0111 0001 =113 updated p2 = 0101 0010 =82
With indicator 3rd LSB set, p1 = 0111 0101 =
117
No pair is selected as
dmax1 − dmax2 < (= 5); hence this block
is skipped with indicator 3rd LSB of p4 set to 0.
Updated p4 = 0100 0101 = 69
p1p3; p1 < p3 so,01 is substituted in last 2
LSB of p1 and 10 in p3 . p1 =75=0100 1011
updated p1 = 0100 1001 =73 p3 =116=0111
0100 updated p3 =0111 0110=118 With
indicator 3rd LSB set, p1 = 0100 1101 = 77
TABLE III: Different image quality metrics comparison with PVD [13] and OPAP [24] for selected standard images.
Image Name
Baboon
Rice
Mandi
Peeper
House
Tree
Sailboat
Boat
Bridge
Aerial
Capacity (bits)
PVD
MSE
PSNR
3088
3088
3088
3088
3088
3088
3088
3088
3088
3088
0.5283
0.4011
0.1007
0.1340
0.2332
0.1292
0.2568
0.1316
0.2751
0.3673
50.9018
52.0979
58.0995
56.8597
54.4527
57.0193
54.0355
56.9395
53.7359
52.4803
SSIM Capacity (bits)
0.9996
0.9995
0.9994
0.9998
0.9992
0.9989
0.9997
0.9990
0.9997
0.9997
3088
3088
3088
3088
3088
3088
3088
3088
3088
3088
message 10 times and then same is done for 10 different secret
messages. Capacity of a cover image is commonly defined as
the maximum number of bits that could be embedded in a
fixed size image. Due to use of compression of secret message
before embedding and compression of cover image itself it is
very difficult to define capacity in a generic way. Some authors
define capacity as the number of bits embedded per pixel of
cover image.In this study we have reported absolute size of
secret message that has been embedded in each case. Reported
image quality metrics in table III are the averages taken over
100 such runs. Simulations were implemented and executed in
Matlab 2015. Results are compared with classical PVD [13]
and OPAP [24] using some standard image quality parameters
such as mean square error (MSE), peak noise to signal ratio
(PSNR) and SSIM. MSE represents the distortion introduced
to the cover image due to embedding of hidden bits. MSE is
OPAP
MSE PSNR
0.0471
0.0471
0.0471
0.0471
0.0471
0.0471
0.0471
0.0471
0.0471
0.0471
61.3988
59.5629
61.3988
61.3988
57.3846
59.0864
55.5833
57.9992
55.9662
59.6495
SSIM Capacity (bits)
Proposed
MSE PSNR
SSIM
1.0000
0.9998
0.9996
0.9998
0.9995
0.9995
0.9997
0.9995
0.9999
0.9999
0.0637
0.0587
0.0292
0.0463
0.0753
0.0664
0.0665
0.0580
0.0579
0.0890
0.9999
0.9998
0.9998
0.9999
0.9999
0.9999
0.9999
0.9997
0.9999
0.9999
3088
3088
1760
2172
3088
3088
3088
2456
3088
3088
60.0890
60.4466
63.4716
61.4726
59.3654
59.9107
59.9037
60.4978
60.5058
58.6382
defined as,
m−1 n−1
1 XX
[I(i, j) − K(i, j)]2 ,
M SE =
mn i=0 j=0
where I denotes the unaltered original cover image and K is
the stego image with embedded bits. Similarly, PSNR for an
8-bit grayscale image can be calculated as:
M AXi2
)
M SE
Visual perceptual changes are very much negligible with the
proposed scheme as can be seen in figure 4. Histograms for the
original and stego images are shown in figure 5 for selected
cover images. LSB bit plane plots are also compared between
the original image and the stego image in figure 6 for selected
images. Both histograms look similar without any subtle
change in pattern. LSB bit-planes are also completely random
without any patch or pattern in stego images. Histogram
P SN R = 10 × log10 (
original
embedded
original
embedded
original
embedded
Fig. 6: LSB bit plane plot of Original and Stego (Embedded)
Image of Baboon (top), Boat and Lenna (bottom).
and LSB bit plane analysis does not show any indication of
hidden data. It is also observed from the results that proposed
method has improved quality metrics with added security
and robustness but with compromise on capacity. Proposed
technique may be helpful with smaller payload and greater
undetectability.
V. C ONCLUSION
The Pixel Value Differencing (PVD) is a well established
technique in image steganography that has high capacity (using
range table)but it suffers from histogram based steganalysis
attacks [22]. OTP encryption is most secure when used with a
random key of comparable size. We have combined the goods
of PVD with the security of OTP. A random generated key
is used to scramble the secret message bits before embedding
into the cover image using 2×2 non-overlapping pixel blocks.
Proposed scheme does not use range table to increase the
capacity as that hampers PSNR greatly with increase in noise
level. Simulations show that this scheme gives better quality
cover image when compared to some well-known techniques.
We focus more on the image undetectability than capacity. So
this technique may be used for smaller hidden messages. If
required capacity can be enhanced by employing a range-table
but with compromised image quality. As a future direction
OTP could be combined with edge detection techniques to
increase the hiding capacity with more bits per pixel.
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