The Image Steganography Techniques

Published Date: 02 Nov 2017

Abstract— Steganography is a method of secret

Communication that hides the existence of secret Data. It can be defined as the study of invisible communication that usually deals with the ways of hiding the existence of the communicated data. The hidden data may be text, image, audio, video etc .The files can be a c image after inserting the message into the cover image using stego-key is called as stego-image. Steganography is now more important to the exponential growth and secret communication of potential computer users on the internet. Various steganographic techniques are analyzed and its pros and cons are highlighted in this paper.

Keyword- Adaptive pixel pair matching(APPM)

Diamond encoding (DE), exploiting modification

direction (EMD), least significant bit (LSB)

optimal pixel adjustment process (OPAP), pixel

pair matching (PPM). pixel value differencing

(PVD)Grey level modification(GLM), Parity

Checker Method(PCM)

I. INTRODUCTION

Now a day, a lot of applications are Internet -based and in some cases it is desired that the communication can be made secretly. There are two techniques are available to achieve the goal One is cryptography where the sender uses an encryption key to encrypt the data, this encrypted data is transmitted through the insecure public channel, and decryption algorithm is used to decrypt the data. The reconstruction of the original data is possible only if the receiver has the key. Another method is steganography, where the secret message

is inserted in some medium like text, audio, image and video. Steganography is an art of hiding information through original files in such a manner that the existence of the message is unknown. The term steganography comes from the Greek word Steganos means, "Covered Writing". The original data can be referred to as cover audio, cover text, or cover image. After inserting the secret data it is referred to as a stego-medium. A stego-key is used for hiding to restrict detection and/or recovery of the embedded data. The cryptography to protect the contents of data, steganography hides the message so that eaves dropper cannot see the message.[1]

It can be used for digital watermarking, ecommerce, and transport of sensitive data. Digital watermarking to be involves embedding hidden image or file to show ownership. This is useful for protecting copyright of the owner. In currently e-commerce transactions, mostly users are protected by a username and Password. But there is no real method of verifying that the user is the actual card holder. Biometric finger print scanning which is combined with unique session IDs embedded into the fingerprint images via steganography, to allow for a very secure option to open e-commerce transaction verification.

II. KINDS OF STEGANOGRAPHY

Steganography can be used for main categories of file formats like, text, images, audio/video, and protocol.

Hiding information in text is the important method of steganography. The method was to hiding a secret message in every nth letter of every word of a text message. After booming of Internet and different type of digital file formats it has decreased in importance. Text stenography using digital files is not used very often because the text files have a very small amount of data.

Methods

Text steganography in mark-up languages (HTML)

Text steganography in specific characters in words

Line shifting method

Word shifting

Open Spaces

Semantic methods

Character encoding

B. Image Steganography:

Image Steganography are used as the popular cover objects. A data is embedded in a digital image using embedded algorithm, using the secret key. The resulting stego image sends to the receiver. On the other hand, it is processed by the extraction algorithm using the same key. During the transmission of stego image unauthenticated persons can only notice the transmission of an image but can’t guess the existence of the hidden data.

C .Audio steganography:

Audio stenography is masking, which is exploits the property of the human ear to hiding information it is not seen. It has been an audible, sound can be inaudible in the presence of another louder audible sound .This property allows to select the channel in which to hide information. Although, it is also similar to images in steganographic slightly mentioned, the larger size of meaningful audio files makes them less popular to use than images.

To embed data secretly onto digital audio there are few techniques introduced:

LSB Coding

Phase Coding

Parity Coding

Spread Spectrum

D. Protocol Steganography:

The protocol steganography is to be embedded information within network protocols such as TCP/IP. We hide an example of it is information in the header of a TCP/IP packet in some fields that can be either optional or are never used.[2]

III. TECHNIQUES OF STEGANOGRAPHY

This paper introduced various techniques of steganography for hiding data in images. The images are represented by numerical values of each pixel value. Where, the value represents the color and intensity of the pixel.

Mainly there are two types of Images:

8-bit images:

In these 8-bit images maximum numbers of colors that can be present are only 256 colors.

24-bit images:

In these images each pixel have 24 bit value in which each 8 bit value refers to three colors red ,blue and green.

Steganography techniques used for image file format can be classified into Spatial domain technique, Masking and filtering, Transform techniques, Distortion Techniques.

A. Spatial Domain Technique:

There are many versions of spatial steganography; all the methods directly change some bits in the image pixel values to hide data. Least significant bit (LSB)-based steganography is one of the simplest techniques that hides a secret message in the LSBs of pixel values without introducing many perceptible distortions. To our human eye, changes in the value of the LSB are imperceptible. Embedding of message bits can be done either sequentially or randomly. These Least Significant Bit (LSB) replacement, LSB matching, Matrix embeds and represent Pixel value, differencing are some of the spatial domain techniques.

B. Masking and Filtering:

In hiding information by marking an image, in the same way as to paper watermarks in these techniques restricted 24 bits and gray scale images. These techniques embed the information in the more significant areas than just hiding it into the noise level. In this case hidden message is more integral to the cover image. Watermarking techniques can be applied without the fear of image destruction due to lossy compression as they are more integrated into the image.

C .Transform Domain Technique:

This is a more complex way of hiding information in an image. Various Algorithms and transformations are used on the image to hiding information in it. Transform domain embedding can be used as a domain of embedding techniques for which a number of algorithms have been suggested [3] .The process of embedding data in the frequency domain of a signal is much stronger than embedding principles that operate in the time domain. Most of the strong steganography systems today operate within the transform domain Transform domain techniques have an advantage over LSB techniques as they hide information in areas of the image that are less exposed in , cropping, compression and image processing. Some transform domain techniques do not seem dependent on the image format and they may out run lossless and lossy format conversions. Transform domain techniques are classified into:

1.Discrete Fourier transformation technique (DFT).

2 Discrete cosine transformation technique (DCT).

3.Discrete Wavelet transformation technique (DWT).

1) Discrete Fourier Transformation Techniques (DFT) are:

This technique used to transfer an image from the spatial domain into the frequency domain. Fourier Transform (FT) methods introduce round off errors, it is not suitable for hidden communication. The difference between a Discrete Fourier Transform and a Discrete Cosine Transform is that the DCT used for only real numbers, A Fourier transform can use only complex numbers.

2) The Discrete Cosine Transform (DCT):

DCT is a popular signal transformation method; it is making use of cosine functions of different frequencies. There are several variants of the DCT with a few modifications in definitions and properties, such that DCT I, II, III, IV, V-VIII with the corresponding inverse formulas. Among these types the DCT II, is usually used in image processing and compression (JPEG, MPEG), because it has a strong energy compaction, that a few coefficients should be enclose the most of the signal in process.

The DCT transforms a cover image from an image representation into a frequency representation, by dividing the image pixels into blocks of 8×8 pixels and then compute the two-dimensional DCT for each block and transforms the pixel blocks into 64 DCT each coefficient. These modifications of a single DCT coefficient will affect all 64 image pixels in that block. The DCT coefficients of the transformed cover image can be quantized, such that coded according to the secret message. The secret data are embedded in the carrier image for DCT coefficients lower than the threshold value. To avoid visual distortion, insertion of secret information is avoided for DCT coefficient value of 0. Insertion and extraction of secret image is an important part for any steganographic technique. It separates the image into parts of differing in importance. It can separate the image should be high, frequency components are middle and low.

3. Discrete Wavelet Transform (DWT):

A Wavelet is simple; a small wave which has its energy concentrated in time to give a tool for the analysis is transient, non-stationary or time-varying phenomena. A signal can be better expressed as a linear decomposition of sums of products of coefficient and functions. Systems with two-parameters are constructed, with one having a double sum and two indices coefficient. The set of coefficients is called as DWT of a signal. The wavelet transform is used to convert a spatial domain into frequency domain components. These wavelets are used for image stenographic model is that the wavelet transform separates the high frequency and low frequency information on a pixel by pixel basis. Discrete Wavelet Transform (DWT) is always preferred over Discrete Cosine Transforms (DCT) because of various level images in low frequency can offer a corresponding resolution needed. The use of DWT transforms mainly address the capacity of the Information-

hiding system features and robustness. The hierarchical nature of the Wavelet representation allows multi-resolution detection of the hidden message, which is a Gaussian distributed random vector added to all the high pass bands in the Wavelet domain.

4) Distortion Techniques:

This technique are needed knowledge of the original cover image the decoding process where the decoder functions to check for differences between the original cover image and the distorted cover image in order to restore the message in secret. The encoder adds a sequence of changes to the cover image. So, information is described as being stored by signal distortion [4].Using this technique, a stego object is created by applying a sequence of modifications of the cover image. This sequence of modifications is used to match the secret message required to transmit [5].The message is encoded by pseudo-randomly chosen pixels. If the stego-image is different from the cover image at the given message pixel, the message bit is a "1."Otherwise, the message bit is a "0." The encoder can modify the "1" value pixels in such a manner that the statistical properties of the image is not affected. According, the need for sending the cover image limits the benefits of this technique. In any steganography technique, the cover image should never be used more than once. If an attacker tampers with the stego-images by scaling, cropping or rotating, the receiver can easily detect it. In some cases, if the message is encoded with information should be error correcting, the change can even be reversed and the original message can be recovered [6].

The steganography techniques pros and cons have

Being listed in the TABLE I with the brief descriptions as follows.

TABLE I

Steganography Techniques

S.No

Techniques

Advantages

Disadvantages

1

Spatial domain technique

i) It is less chance for degradation of the original image.

ii)There is a Hiding capacity is more (i.e.) more information can be stored in an image

i)The

hidden data

can be lost

with

image manipulation, less robust

ii) It is

Hidden data

can be

easily

destroyed

by simple attacks

2

Masking and Filtering

i) It is more robust than LSB replacement with respect to the compression

techniques.

ii) The data to be hidden in the visible parts of the image.

These techniques

can be

applied only

to gray

scale images and restricted to

24 bits.

3

Transform Domain Technique

i) Hiding information in more significant areas of the cover-image, it make them more robust to attack than LSB.

ii) It can be applied Transformations to the entire image, to block throughout the image, or another variants.

These method types are computationally complex.

IV.DATA HIDING MEDTHODS

Several methods are available in literature for hiding data, they are Least Significant bit(LSB),Pixel value differencing(PVD),Gray level

Modification (GLM), Parity checker method(PCM),Diamond encoding method(DEM),Optimal pixel Adjustment process(OPAP),Exploiting modification direction(EMD),Adaptive pixel pair matching(APPM).

A .Least Significant Bit Method (LSB):

This method is least significant bit of pixel value is used for insertion of the message [8], LSB is easy to implement.

B. Pixel value differencing Method (PVD):

This method can successfully provide both outstanding imperceptibility and high embedding capacity for the stego-image [9]. The pixel value differencing (PVD) method is segmented the cover image into non-overlapping blocks are containby two connecting pixels and modifies the pixel difference in each block (pair) for data embedding. A larger difference in the original pixel values allows a greater modification.

C. Gray level modification Method (GLM):

Gray level modification is defined as a technique in which the gray level values of the image pixels are modified in representing binary data[10] .Each pixel has a distinct gray level value which can have an odd or even value of pixels. According, this odd or even value of the gray level appropriately modified to represent binary data.

D. Parity Checker Method (PCM):

This method used for odd and even parity pixels. This method, 0 can be inserted at a pixel location if that pixel has odd parity. The odd value is the number of 1’s in the binary value of the pixel. Similarly, 1 can be inserted at a pixel location if that pixel has even parity. The even value should be number of 1’s in the binary value of pixel[11] .If the corresponding parity does not exist at a pixel location either for 0 or 1, it has made corresponding parity at that pixel location (odd parity for 0 and even parity for 1) by adding or subtracting 1 to the pixel location. According, the change in the image quality cannot be visible to the human visual system (HVS).

E. Exploiting modification direction method (EMD):

This method in which only one pixel pair is changed one gray-scale unit and message digit in a 5 –ary notational system can be embedded [12]. These methods are not suitable for applications requiring high payload.

F. Diamond encoding Method:

This diamond encoding method based on pixel pair matching position. Diamond encoding greatly enhances the payload of EMD while acceptable stego image quality [12].There are several problems; the payload is determined selected notational system. The notational system cannot be arbitrarily selected.

G. Optimal pixel adjustment process method (OPAP):

These method simple and efficient optimal pixel adjustment processes to reduce the distortion by the LSB replacement [12]. However, if the adjusted result of smaller distortion, these message bits are either replaced by the adjusted results or otherwise kept unmodified.

H. Adaptive pixel pair matching method (APPM):

LSBAn adaptive data hiding method based on pixel pair matching [12]. The idea of pixel pair matching is to use the values of reference coordinate and search coordinate in neighbourhood set of the pixel pair according to the given message digit. These methods always lower distortion in various payloads.

PVD

Image Steganography method

GLM

PCM

DE

OPAP

EMD

APPM

Figure 2.Various steganography methods

The steganography methods pros and cons have been listed in the TABLE I I with the brief described as follows:

TABLE II

Steganography Methods

S.No

Method

Advantages

Disadvantages

1

LSB Method[8]

Least significant bits of pixel value is used for insertion of data. This method is easy to implement.

i). Message can be easily recovered by the unauthorized person as message is in LSB.

ii) As message is hidden in LSB, so intruder can modify the LSB of all the image pixels in the way the

hidden message can be destroyed.

3. LSB is most vulnerable to hardware imperfection or quantization of noise.

2

PVD Method[9]

It can be successfully provide both high capacity embedding and outstanding imperceptibility of the stego-image.

The pixel value differencing (PVD) method segments the cover image into non overlapping blocks that containing two connecting pixels and modifies the pixel difference in each block (pair) for data

Embedding. A larger difference in the original pixel values allows a greater modification

3

GLM Method[10]

It has low computational complexity, high information hiding capacity

Only one-to-one mapping between binary data. Data loss from image modification. Low embedding capacity.

4

Parity Checker Method [11]

Odd and even parity for insertion and retrieval of messages.

Retrieval of message bits from all the locations.

By adding or subtracting 1 to the pixel location such that the change in the image quality should

Not be visible to the human visual system (HVS).

5

Diamond encoding Method[12]

The diamond encoding technique

Minimizes the distortion to perform better visual quality. Embedding digits in larger notational system.

The payload of DE is determined by the selected notational system. The notational system cannot be arbitrarily selected.

6

OPAP method[12]

Reduce the Distortion

Smaller Distortion

7

EMD method[12]

EMD is a only one pixel in a pixel pair is changed one gray-scale unit a message digit in a 5-ary notational system can be embedded to provide better stego image quality.

The maximum capacity of EMD is 1.161bpp

8

APPM Method[12]

APPM allows users to select digits in any notational system for data embedding to achieve better image quality.

Security is not applied.

V.IMAGE BASED STEGANALYSIS

Steganalysis is the science of detecting hidden data. The objective of steganalysis is to break steganography and the detection of stego image is the goal of steganalysis. Mostly all steganalysis algorithms rely on steganographic algorithms introducing statistical differences between cover and stego image. This deals with three important categories of Steganalysis:

1)Visual attacks: it reveals the presence of hidden data, which helps to separate the image into bit planes for further more analysis

2) Statistical attacks: These types of attacks are more powerful and successful, because they are reveal the smallest alterations in an images statistical behaviour. Statistical attacks may be passive or active. Passive attacks involves with identifying presence or absence of a covert message or embedding algorithm used. An active attack is used to investigate embedded message length or hidden message location or secret key used in embedding.

3) Structural attacks: The format of the data files changes as the data hidden and embedded; identifying these characteristic structure changes can help us to find the presence of image.

VI.STEGANALYTIC TOOLS

There are several steganalysis tools available in market like Photo Title, 2Mosaic and Stir Mark Benchmark etc. These three steganalysis tools can remove steganographic content from any image.

This is achieved by destroying secret message by two techniques: break apart and resample. StegDetect, StegBreak, StegSpy identify the information embedded via the following tools -, JPhide, and Outguess 0.13b, Jsteg-shell

Invisible Secrets,Camouflage , appendX , F5, , Hiderman, JPHIde and Seek, Masker, JPegX, Steganography Analyzer Real-Time Scanner is the best available steganalysis software in the market at the moment, which can analyze all the network traffic to look for traces of steganographic communication.

The steganalysis tools have been listed in the TABLE III with the brief descriptions as follows.

TABLE III

Steganalysis Tools[13]

S.No

Tools

Website

1

EzStego

online.securityfocus.com/tools/586/scoreit

2

F5

wwwrn.inf.tu-dresden.de/~westfeld/f5.html

3

Hide and Seek v4.1

ftp://ftp.csua.berkeley.edu/pub/cypherpunks/steganography

4

Hide and Seek for Win95

ftp.hacktic.nl/pub/crypto/incoming/

5

Hide4PGP

www.heinz-repp.onlinehome.de/Hide4PGP.htm

6

Jpeg-Jsteg

ftp://ftp.funet.fi/pub/crypt/steganography/

7

MandelSteg

ftp://idea.sec.dsi.unimi.it/pub/security/crypt/code/

8

MP3Stego

www.cl.cam.ac.uk/~fapp2/steganography/

mp3stego/

9

OutGuess

www.outguess.org/download.php

10

Steganos

www.steganos.com/en/

11

S-Tools v4

Members.tripod.com/steganography/stego/s-tools4.html

12

White Noice Storm

ftp://ftp.esua.berkely.edu/pub/cypherpunks/steganography/

VII.Conclusion

In this paper study of different methods of steganography are discussed. Each method has the procedure of embedding in itself. Each method has advantages, and some disadvantages in comparison with other methods of steganography. So predicting a best method is not possible. It is also impossible to determine the worst one. We have compared them from different aspects of method, which results in determining a suitable method for a specific use. It can help for the reader to understand why an algorithm is better than another in a specific situation. It may be concluded that steganographic algorithms developed for one cover media may not be effective for another media. The research to devise a strong steganographic technique is a continuous process and still going on.