An introduction to steganography methods

Abstract

In this paper, we are going to introduce different types of steganography considering the cover data. As the first step, we will talk about text steganography and investigate its details. Then, image steganography and its techniques will be investigated. Some techniques including Least Significant Bits, Masking and filtering and Transformations will be subjected during image steganography. Finally, audio steganography which contains LSB Coding, Phase Coding, Spread Spectrum and Echo Hiding techniques will be described.

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World Applied Programming, Vol (1), No (3), August 2011. 191-195
ISSN: 2222-2510
©2011 WAP journal. www.waprogramming.com
191
An introduction to steganography methods
Mehdi Hariri Ronak Karimi Masoud Nosrati *
Kermanshah University of Kermanshah University of Kermanshah University of Medical Science, Medical Science, Medical Science, Kermanshah, Iran Kermanshah, Iran Kermanshah, Iran mehdi.hariri@yahoo.com rk_respina_67@yahoo.com minibigs_m@yahoo.co.uk
Abstract: In this paper, we are going to introduce different types of steganography considering the cover data.
As the first step, we will talk about text steganography and investigate its details. Then, image steganography
and its techniques will be investigated. Some techniques including Least Significant Bits, Masking and filtering
and Transformations will be subjected during image steganography. Finally, audio steganography which
contains LSB Coding, Phase Coding, Spread Spectrum and Echo Hiding techniques will be described.
Key word: Steganography • text steganography • image steganography • audio steganography
I. INTRODUCTION
The word steganography is derived from the Greek words “stegos” meaning “cover” and “grafia” meaning “writing”
defining it as “covered writing” [1]. Steganography is one such pro-security innovation in which secret data is embedded
in a cover [2]. The notion of data hiding or steganography was first introduced with the example of prisoners' secret
message by Simmons in 1983 [3].
Steganography and cryptography are closely related. Cryptography scrambles messages so they cannot be
understood. Steganography on the other hand, will hide the message so there is no knowledge of the existence of the
message in the first place. In some situations, sending an encrypted message will arouse suspicion while an”invisible”
message will not do so. Both sciences can be combined to produce better protection of the message. In this case, when
the steganography fails and the message can be detected, it is still of no use as it is encrypted using cryptography
techniques. [4]
There exist two types of materials in steganography: message and carrier. Message is the secret data that should be
hidden and carrier is the material that takes the message in it [5].
There are many types of steganography methods. In this paper, we are going to take a short look at different
steganography methods. Fig. 1 below shows the different categories of file formats that can be used for steganography
techniques [6].
Fig.1 Steganography types diagram
In the second section, text steganography will be talked. Then we will get into images steganography principals in
the third section. Finally audio steganography will be investigated.
Steganography
Text Image Audio

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II. TEXT STEGANOGRAPHY
Text steganography can be achieved by altering the text formatting, or by altering certain characteristics of textual
elements (e.g., characters). The goal in the design of coding methods is to develop alterations that are reliably decodable
(even in the presence of noise) yet largely indiscernible to the reader. These criteria, reliable decoding and minimum
visible change, are somewhat conflicting; herein lies the challenge in designing document marking techniques. The
document format file is a computer file describing the document content and page layout (or formatting), using standard
format description languages such as PostScript2, TeX, @off, etc. It is from this format file that the image - what the
reader sees - is generated.
The three coding techniques that we propose illustrate different approaches rather than form <an exhaustive list of
document marking techniques. The techniques can be used either separately or jointly. Each technique enjoys certain
advantages or applicability as we discuss below.
Line-Shift Coding
This is a method of altering a document by vertically shifting the locations of text lines to encode the document
uniquely. This encoding may be applied either to the format file or to the bitmap of a page image. The embedded
codeword may be extracted from the format file or bitmap. In certain cases this decoding can be accomplished without
need of the original image, since the original is known to have uniform line spacing between adjacent lines within a
paragraph.
Word-Shift Coding
This is a method of altering a document by horizontally shifting the locations of words within text lines to encode
the document uniquely. This encoding can be applied to either the format file or to the bitmap of a page image. Decoding
may be performed from the format file or bitmap. The method is applicable only to documents with variable spacing
between adjacent words. Variable spacing in text documents is commonly used to distribute white space when justifying
text. Because of this variable spacing, decoding requires the original image - or more specifically, the spacing between
words in the un-encoded document.
Feature Coding
This is a coding method that is applied either to a format file or to a bitmap image of a document. The image is
examined for chosen text features, and those features are altered, or not altered, depending on the codeword. Decoding
requires the original image, or more specifically, a specification of the change in pixels at a feature. There are many
possible choices of text features; here, we choose to alter upward, vertical endlines - that is the tops of letters, b, d, h, etc.
These endlines are altered by extending or shortening their lengths by one (or more) pixels, but otherwise not changing
the endline feature [7].
There is another form of text steganography which is defined by Chapman et al. as the text steganography is a method
of using written natural language to conceal a secret message [8].
III. IMAGE STEGANOGRAPHY
Hiding information inside images is a popular technique nowadays. An image with a secret message inside can easily
be spread over the World Wide Web or in newsgroups. The use of steganography in newsgroups has been researched by
German steganographic expert Niels Provos, who created a scanning cluster which detects the presence of hidden
messages inside images that were posted on the net. However, after checking one million images, no hidden messages
were found, so the practical use of steganography still seems to be limited.
To hide a message inside an image without changing its visible properties, the cover source can be altered in ”noisy”
areas with many color variations, so less attention will be drawn to the modifications. The most common methods to make
these alterations involve the usage of the least-significant bit or LSB, masking, filtering and transformations on the cover
image. These techniques can be used with varying degrees of success on different types of image files.

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193
Least Significant Bits
A simple approach for embedding information in cover image is using Least Significant Bits (LSB). The simplest
steganography techniques embed the bits of the message directly into least significant bit plane of the cover image in a
deterministic sequence. Modulating the least significant bit does not result in human-perceptible difference because the
amplitude of the change is small [9]. To hide a secret message inside an image, a proper cover image is needed. Because
this method uses bits of each pixel in the image, it is necessary to use a lossless compression format, otherwise the
hidden information will get lost in the transformations of a lossy compression algorithm. When using a 24-bit color
image, a bit of each of the red, green and blue color components can be used, so a total of 3 bits can be stored in each
pixel. For example, the following grid can be considered as 3 pixels of a 24-bit color image, using 9 bytes of memory:
(00100111 11101001 11001000)
(00100111 11001000 11101001)
(11001000 00100111 11101001)
When the character A, which binary value equals 10000001, is inserted, the following grid results:
(00100111 11101000 11001000)
(00100110 11001000 11101000)
(11001000 00100111 11101001)
In this case, only three bits needed to be changed to insert the character successfully. On average, only half of the
bits in an image will need to be modified to hide a secret message using the maximal cover size. The result changes that
are made to the least significant bits are too small to be recognized by the human visual system (HVS), so the message is
effectively hidden [4].
As you see, the least significant bit of third color is remained without any changes. It can be used for checking the
correctness of 8 bits which are embedded in these 3 pixels. In other words, it could be used as “parity bit”.
Masking and filtering
Masking and filtering techniques, usually restricted to 24 bits or grayscale images, take a different approach to hiding a
message. These methods are effectively similar to paper watermarks, creating markings in an image. This can be achieved
for example by modifying the luminance of parts of the image. While masking does change the visible properties of an
image, it can be done in such a way that the human eye will not notice the anomalies. Since masking uses visible aspects
of the image, it is more robust than LSB modification with respect to compression, cropping and different kinds of image
processing. The information is not hidden at the ”noise” level but is inside the visible part of the image, which makes it
more suitable than LSB modifications in case a lossy compression algorithm like JPEG is being used [4].
Transformations
A more complex way of hiding a secret inside an image comes with the use and modifications of discrete cosine
transformations. Discrete cosine transformations (DST)), are used by the JPEG compression algorithm to transform
successive 8 x 8 pixel blocks of the image, into 64 DCT coefficients each. Each DCT coefficient F(u, v) of an 8 x 8 block
of image pixels f(x, y) is given by:





++
=∑∑
= =
7
0
7
016)12(
cos
16)12(
cos*),()()(
4
1
),( x y
vyux
yxfvCuCvuF
ππ
,




=
=.1
0
2
1
)( else
x
xC
After calculating the coefficients, the following quantizing operation is performed:






=),( ),(
),( vuQ vuF
vuFQ
Where Q(u, v) is a 64-element quantization table. A simple pseudo-code algorithm to hide a message inside a JPEG image
could look like this [4]:

Masoud Nosrati et al., World Applied Programming, Vol (1), No (3), August 2011.
194
Input: message, cover image
Output: steganographic image containing message
while data left to embed do
get next DCT coefficient from cover image
if DCT 6= 0 and DCT 6= 1 then
get next LSB from message
replace DCT LSB with message bit
end if
insert DCT into steganographic image
end while
IV. AUDIO STEGANOGRAPHY
In audio steganography, secret message is embedded into digitized audio signal which result slight altering of binary
sequence of the corresponding audio file. There are several methods are available for audio steganography. We are going
to have a brief introduction on some of them.
LSB Coding
Sampling technique followed by Quantization converts analog audio signal to digital binary sequence. In this
technique LSB of binary sequence of each sample of digitized audio file is replaced with binary equivalent of secret
message.
Phase Coding
Human Auditory System (HAS) can’t recognize the phase change in audio signal as easy it can recognize noise in the
signal. The phase coding method exploits this fact. This technique encodes the secret message bits as phase shifts in the
phase spectrum of a digital signal, achieving an inaudible encoding in terms of signal-to- noise ratio.
Spread Spectrum
There are two approaches are used in this technique: the direct sequence spread spectrum (DSSS) and frequency
hopping spread spectrum (FHSS). Direct-sequence spread spectrum (DSSS) is a modulation technique used in
telecommunication. As with other spread spectrum technologies, the transmitted signal takes up more bandwidth than the
information signal that is being modulated. Direct-sequence spread-spectrum transmissions multiply the data being
transmitted by a "noise" signal. This noise signal is a pseudorandom sequence of 1 and −1 values, at a frequency much
higher than that of the original signal, thereby spreading the energy of the original signal into a much wider band.
The resulting signal resembles white noise. However, this noise-like signal can be used to exactly reconstruct the
original data at the receiving end, by multiplying it by the same pseudorandom sequence (because 1 × 1 = 1, and −1 × −1
= 1). This process, known as "de-spreading", mathematically constitutes a correlation of the transmitted Pseudorandom
Noise (PN) sequence with the receiver's assumed sequence. For de-spreading to work correctly, transmit and receive
sequences must be synchronized. This requires the receiver to synchronize its sequence with the transmitter's sequence via
some sort of timing search process. In contrast, frequency-hopping spread spectrum pseudo-randomly retunes the carrier,
instead of adding pseudo-random noise to the data, which results in a uniform frequency distribution whose width is
determined by the output range of the pseudo-random number generator [10].
Echo Hiding
In this method the secret message is embedded into cover audio signal as an echo. Three parameters of the echo of the
cover signal namely amplitude, decay rate and offset from original signal are varied to represent encoded secret binary
message. They are set below to the threshold of Human Auditory System (HAS) so that echo can’t be easily resolved.
Video files are generally consists of images and sounds, so most of the relevant techniques for hiding data into images
and audio are also applicable to video media. In the case of Video steganography sender sends the secret message to the
recipient using a video sequence as cover media. Optional secret key ‘K’ can also be used during embedding the secret
message to the cover media to produce ‘stego-video’. After that the stego-video is communicated over public channel to
the receiver. At the receiving end, receiver uses the secret key along with the extracting algorithm to extract the secret
message from the stego-object.

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The original cover video consists of frames represented by Ck(m,n) where 1 £ k £ N. ‘N’ is the total number of frame
and m,n are the row and column indices of the pixels, respectively. The binary secret message denoted by Mk(m, n) is
embedded into the cover video media by modulating it into a signal. Mk(m, n) is defined over the same domain as the host
Ck(m,n).The stego-video signal is represented by the equation
Sk(m, n) = Ck(m, n)+ak (m, n) Mk(m, n) , k = 1, 2, 3 . . .N
Where ak (m, n) is a scaling factor. For simplicity ak (m, n) can be considered to be constant over all the pixels and
frames. So the equation becomes [11]:
Sk(m, n) = Ck(m, n)+a (m, n) Mk(m, n) , k = 1, 2, 3 . . .N
V. CONCLUSION
In this paper, we talked about steganography and its types. First we had a look at text steganography and Line-Shift
Coding, Word-Shift Coding and Feature Coding techniques as different methods of it. Then we got into image
steganography and introduced LSB, Masking and filtering and Transformations. As the ending part, Audio steganography
was talked and LSB Coding, Phase Coding, Spread Spectrum and Echo Hiding were investigated.
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