Study and Comparison of Digital Image Steganography · Study and Comparison of Digital Image Steganography ... The steganographic methods are classified in to ... protocol steganography.

National Conference on “Advanced Technologies in Computing and Networking"-ATCON-2015Special Issue of International Journal of Electronics, Communication & Soft Computing Science and Engineering, ISSN: 2277-9477

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Study and Comparison of Digital Image Steganography

Priyanka A. Sawarkar Shraddha D. Nimkale Prof. V.S. Belsare

Abstract — Steganography is the art of hiding the fact thatcommunication is taking place, by The Wrapping information inother information. Many different carrier file formats can beused, but digital images are the most popular because of theirfrequency on the internet. For hiding secret information inimages, there exists a large variety of steganography techniquessome are more complex than others and all of them haverespective strong and weak points. Different applications mayrequire absolute invisibility of the secret information, whileothers require a large secret message to be hidden. This paperintends to give an overview of image Steganography, its uses andtechniques. It also attempts to identify the requirements of a goodSteganography.

Keywords: Steganography, wrapping information,Absoluteinvisibility.

I. INTRODUCTIONThe secrecy and safety of communication data is

more important in our daily life. Today’s people usingdifferent ways for communication like internet or telephone,but it isn’t always safe. For securing the secrecy ofcommunication to encrypt and decrypt data in order to keepthe message secrete by cryptography technique. Unfortunatelyit is sometimes not enough to keep the contents of a messagesecrete, it can also be important to keep existence of messagesecret. To implement this technique is called Steganography.Steganogrephy is “Art of Hiding” which means ‘Writing inHiding’ is to hide data in a cover media. Steganography can beuse to hide or cover the existence of communication ofencrypted data.

The steganographic methods are classified in tospatial domain embedding and frequency domain embedding.In frequency domain images are transformed into frequencycomponent by using DCT,FFT or DWT and then messages areembedded either in bit level or in block level. In spatialdomain LSB replacing is the most widely used data hidingmethod.

II. STEGANOGRAPHY

Steganography is a Greek word which means coveredwriting. The ‘Stegano’ means ‘covered’and ‘graphical’ means‘writing’. Steganographic is not only the art of hiding data butalso hiding the fact of transmission of secrete data. Insteganography, The only recipient knows the existence ofmessage. In ancient time, the data was protected by hiding iton the back of wax, writing tables, stomach of rabbits or onthe scalp of slaves. The Steganography equation is

“stego_medium = cover medium + secrete message + stegokey”[2] .

A) Digital Mediums of Steganography:Today’s most of people transmit the data in the form of text,image, audio as well as video over the medium.[3]

A.1) Digital Image for Steganography: Taking the coverobject as image in steganography is known as imagesteganography. Generally, in this technique pixel intensitiesare used to hide the information.

A.2)Network Protocol for Steganography:When takingcover object as network protocol, such as TCP, DP, ICMP, IPetc, where protocol is used as carrier, is known as networkprotocol steganography. In the OSI network layer model thereexist covert channels where steganography can be achieved inunused header bits of TCP/IP fields [9].

A.3) Video for Steganography:Video Steganography is atechnique to hide any kind of files or information into digitalvideo format. Video (combination of pictures) is used ascarrier for hidden information. Generally discrete cosinetransform (DCT) alter values (e.g., 8.667 to 9) which is usedto hide the information in each of the images in the video,which is not noticeable by the human eye. Videosteganography uses such as H.264, Mp4, MPEG, AVI or othervideo formats.

A.4) Audio for Steganography:When taking audio as acarrier for information hiding it is called audio steganography.It has become very significant medium due to voice over IP(VOIP) popularity. Audio steganography uses digital audioformats such as WAVE, MIDI, AVI MPEG or etcforSteganography.

A.5) Text for Steganography:General technique in textsteganography, such as number of tabs, white spaces, capitalletters, just like Morse code [10] and etcis used to achieveinformation hiding.


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A.1 Fig: Digital Medium For Steganography

III. IMAGE STEGANOGRAPHYHiding the data by taking the cover object as image is referredas image Steganography. In image steganography pixelintensities are used to hide the data. In digital steganography,images are widely used cover source because there are numberof bits presents in digital representation of an image

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a) Techniques of Image Steganography:1. Spatial Domain Method2. Transform Domain Technique3. Spread Spectrum Technique4. Distortion Techniques5. Masking and Filtering

Spatial Domain Method:In this method the secret data isembedded directly in the intensity of pixels. It means somepixel values of the image are changed directly during hidingdata. In this, the most common and simplest Steganographymethod is the least significant bits (LSB) insertion method. InLSB technique, least significant bits of the pixels arereplacedby the message bits which are permuted before embedding[1].

Fig: B.1 Spatial Domain Method

a.1) Classification of Spatial Domain

i. Least significant bit (LSB)ii. Pixel value differencing (PVD)iii. Edges based data embedding method (EBE)iv. Random pixel embedding method (RPE)v. Mapping pixel to hidden data method (PMM)vi. Labeling or connectivity methodvii. Pixel intensity or gray level value (GLV)viii. Texture based methodix. Histogram based methodsx. Color Palette based methods

i. LSB Technique: It is one of the most commonand easiest methods for message hiding. In thismethod, message is hidden in the leastsignificant bits of image pixels. Changing theLSB of the pixels does not introduce muchdifference in the image and thus the stego imagelooks similar to the original image. In case of 24-bit images three bits of pixel can be used forLSB substitution as each pixel has separatecomponents for red, green and blue.

ii. PVD Technique: Based on the fact that ourhuman vision is sensitive to slight changes in thesmooth regions, while can tolerate more severechanges in the edge regions, the PVD-basedmethods have been proposed to enhance theembedding capacity without introducing obviousvisual artifacts into stego images. In PVD-basedschemes, the number of embedded bits isdetermined by the difference between the pixeland its neighbor. The larger the differenceamount is, the more secret bits can be embedded.Usually, PVD based approaches can achievemore imperceptible results compared with thosetypical LSB-based approaches with the sameembedding capacity. However, based onextensive experiments and analysis, we find thatmost existing PVD based algorithms performbad to resist some statistical analysis even with alow embedding capacity, e.g. 10% bpp (bit perpixel).

iii. EDGE BASED: Edge Detection algorithmhides secret data into the pixels that make up theextracted edges of the carrier image. The secretdata can be of any type, not necessarily text, andthey are actually concealed into the three LSBs(Least Significant Bits) of the pixels of thecarrier image, but not in every pixel, only in theones that are part of the edges detected by theedge detection algorithm.

iv. RANDOM PIXEL SELECTION: In thisalgorithm data is hidden randomly i.e., data ishidden in some randomly selected pixel.Random pixel is generated by using Fibonaccialgorithm.


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v. PIXEL MAPPING METHOD (MPP):Themethod for information hiding within the spatialdomain of an image. Embedding pixels areselected based on some mathematical functionwhich depends on the pixel intensity value of theseed pixel and its 8 neighbors are selected incounter clockwise direction. Before embedding achecking has been done to find out whether theselected embedding pixels or its neighbors lies atthe boundary of the image or not. Dataembedding are done by mapping each two orfour bits of the secret message in each of theneighbor pixel based on some features of thatpixel.

vi. PIXEL CONNECTIVITY: A morphologicalprocessing starts at the peaks in the markerimage and spreads throughout the rest of theimage based on the connectivity of the pixels.Connectivity defines which pixels are connectedto other pixels. A group of pixels that connectedbased on Connectivity types called an Object.

vii. PIXEL INTENSITY OR GLV: Techniquewhich is used to map data by modifying the graylevel of the image pixels. ModificationSteganography is a technique to map data (notembed or hide it) by modifying the gray levelvalues of the image pixels. This technique usesthe concept of odd and even numbers to mapdata within an image. It is a one-to-one mappingbetween the binary data and the selected pixelsin an image. From a given image a set of pixelsare selected based on a mathematical function.The gray level values of those pixels areexamined and compared with the bit stream thatis to be mapped in the image.

viii. TEXTURE BASED: In this technique the secretand host images are divided into blocks ofspecific size and each block in secret image istaken as a texture pattern for which the mostsimilar block is found among the blocks of thehost image. The embedding procedure is carriedon by replacing these small blocks of the secretimage with blocks in host image in such a waythat least distortion would be imposed on it.

ix. HISTOGRAM BASED: In histogram baseddata hiding technique the crucial informationis embedded into the image histogram. Pairsof peak points and zero points are used toachieve low embedding distortion withrespect to providing low data hiding capacity.

x. PALETTE BASED: The palette based imagesteganography is similar to the commonly usedLSB method for 24 bit color images (or 8 bitgrayscale images). After the palette colors aresorted by luminance, it embeds the message intothe LSB of indices pointing to the palette colors.

Message recovery is simply achieved byselecting the same pixels and collecting theLSBs of all indices to the ordered palette.

Advantages of spatial domain technique are:

1. There is less chance for degradation of the original image.2. More information can be stored in an image.3. Low Mathematical Complexity.

Disadvantages of LSB technique are:

1. Less robust, the hidden data can be lost with imagemanipulation.2. Hidden data can be easily destroyed by simple attacks.3. The information may be segmented on a particular part ofimage.4. Typically depend on the image format.

TRANSFORM DOMAIN METHODThe transform domain Steganography technique is

used for hiding a large amount of data and provides highsecurity, a good invisibility and no loss of secret message. Thegoal behind that is to hide information in frequency domain byaltering magnitude of all of discrete cosine transform (DCT)coefficients of cover image. The 2-D DCT converts imageblocks from spatial domain to frequency domain. The coverimage is divided into non overlapping blocks of size 8×8andapplies DCT on each of blocks of cover image usingforward DCT.[1].

Transform domain techniques are broadly classifiedinto:A. Discrete Cosine transform (DCT) based techniqueB. Discrete Fourier transform (DFT) based technique.C. Discrete Wavelet transform (DWT) based technique.D. Integer Wavelet Transform (IWT) base techniques.E. Discrete CurveletTransform(DCVT) Base techniques.

A. DISCRETE COSINE TRANSFORM (DCT) BASEDTECHNIQUE:DCT is a general orthogonal transform fordigital image processing and signal processing withadvantages such as high compression ratio, small bit error rate,good information integration ability and good synthetic effectof calculation complexity. DCT allows an image to be brokenup into different frequency bands namely the high, middle andlow frequency bands thus making it easier to choose the bandin which the watermark is to be inserted [3]. The literaturesurvey reveals that mostly the middle frequency bandsare chosen because embedding the information in amiddle frequency band does not scatter the watermarkinformation to most visual important parts of the imagei.e. the low frequencies and also it do not overexposethem to removal through compression and noise attackswhere high frequency components are targeted. Numerous


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watermarking techniques based on DCT are proposed.Although some of the watermarking techniques embed thewatermark in the DC component, most techniques utilize thecomparison of middle band DCT coefficients to embed asingle bit of information into a DCT block.B. DISCRETE FOURIER TRANSFORM (DFT) BASEDTECHNIQUE: The DFT based technique is similar to theDCT based technique but it utilizes the Fourier transforminstead of cosine which makes it lack resistance to stronggeometric distortions. Although it increases the overallcomplexity of the process.C. DWT BASED TECHNIQUE: A wavelet is a small wavewhich oscillates and decays in the time domain. The DiscreteWavelet Transform (DWT) is a relatively recent andcomputationally efficient technique in computer science.Wavelet analysis is advantageous as it performs local analysisand multi-resolution analysis. To analyze a signal at differentfrequencies with different resolutions is called multi-resolution analysis (MRA). This method transforms the objectin wavelet domain, processes the coefficients and thenperforms inverse wavelet transform to represent the originalformat of the stego object.D. IWT BASED: Since the discrete wavelet transform allowsindependent processing of the resulting components withoutsignificant perceptible interaction between them, hence it isexpected to make the process of imperceptible embeddingmore effective. However, the used wavelet filters (and also theother filters like DCT, FFT) have floating point coefficients.Thus, when the input data consist of sequences of integers (asin the case for images), the resulting filtered outputs no longerconsist of integers, which doesn't allow perfect reconstructionof the original image. However, with the introduction ofWavelet transforms that map integers to integers the outputcan be completely characterized with integers [8].E. DCVT BASED: Curve let transform is the new member ofthe evolving family of multistate geometric transforms [11].Since it represents edges better than Wavelet, Curve lettransform offers an effective solution to the problemsassociated with image steganography using Wavelets andDCT (Discrete Cosine Transform).

Advantages of transform domain technique are:1. There is less chance for removal or loss of the hidden data.2. Information is distributed over all whole image.3. Provides much higher flexibility for hiding data.4. Typically independent of the image format.

Disadvantages of transform technique are:1. Greater understanding of the embedding domain required.2. Careful selection of embedding coefficients requiredotherwise it can cause degradation of image.3. Higher Mathematical Complexity.4. Relatively Low embedding capacity.Distortion Techniques:Distortion techniques needknowledge of the original cover image during the decoding

process where the decoder functions to check for differencesbetween the original cover image and the distorted coverimage in order to restore the secret message. The encoder addsa sequence of changes to the cover image. So, information isdescribed as being stored by signal distortion[5]. Using thistechnique, a stego object is created by applying a sequence ofmodifications to the cover image. This sequence ofmodifications is use to match the secret message required totransmit [6].The message is encoded at pseudo-randomlychosen pixels. If the stego-image is different from the coverimage at the given message pixel, the message bit is a “1.”otherwise, the message bit is a “0.” The encoder can modifythe “1” value pixels in such a manner that the statisticalproperties of the image are not affected. However, the need forsending the cover image limits the benefits of this technique.In any steganographic technique, the cover image shouldnever be used more than once. If an attacker tampers with thestego-image by cropping, scaling or rotating, the receiver caneasily detect it. In some cases, if the message is encoded witherror correcting information, the change can even be reversedand the original message can be recovered [7].Masking and Filtering: These techniques hide information bymarking an image, in the same way as to paper watermarks.These techniques embed the information in the moresignificant areas than just hiding it into the noise level. Thehidden message is more integral to the cover image.Watermarking techniques can be applied without the fear ofimage destruction due to lossy compression as they are moreintegrated into the image. [3]

Advantages of Masking and filtering Techniques:1. This method is much more robust than LSB replacementwith respect to compression since the information is hidden inthe visible parts of the image.

Disadvantages of Masking and filtering Techniques:1. Techniques can be applied only to gray scale images andrestricted to 24 bits

Spread Spectrum Technique:The concept of spreadspectrum is used in this technique. In this method the secretdata is spread over a wide frequency bandwidth. The ratio ofsignal to noise in every frequency band must be so small thatit becomes difficult to detect the presence of data. Even ifparts of data are removed from several bands, there would bestill enough information is present in other bands to recoverthe data. Thus it is difficult to remove the data completelywithout entirely destroying the cover .It is a very robusttechnique mostly used in military communication[8].In thisThe Spread Spectrum Image Steganography (SSIS) of thepresent invention is a data hiding/secret communicationsteganography system which uses digital imagery as a coversignal. Spread spectrum provides the ability to hide asignificant quantity of information bits within digital imageswhile avoiding detection by an observer. The message isrecovered with lowest error probability due the use of error


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control coding. Spread spectrum image Steganographypayload is, at a minimum, an order of magnitude greater thanof existing watermarking techniques. Furthermore, theoriginalimage is not needed to extract the hidden message.The proposed receiver need only possess a key in order toreveal thesecret message. The existence of the hiddeninformation is virtually undetectable by human or computeranalysis. at last,SSIS provides resiliency to transmission noise,like which found in a wireless environment and low levels ofcompression[1].The main idea of SSIS is that of spreading thesecret message over a large frequency bandwidth under thenoise level. SSIS provides the ability to hide and recover, errorfree, a significant quantity of information bits within digitalimages, voiding detection by an observer. Furthermore, SSISis a blind scheme because the original image is not needed toextract the hidden information.

IV. COMPARISON OF DIFFERENT TECHNIQUES

All above techniques for image Steganography have differentstrong and weak point and it is important to ensure that oneuses the most suitable technique for an application. AllSteganographic Techniques have to Complete with few basicrequirements. The most important requirement is that aSteganographic technique has to be invisibility.

Invisibility:- Invisibility of Steganography technique is thefirst and the most important requirement. Since, the strength ofthe Steganography lies in its ability to be invisible by thehuman eyes.

Payload Capacity:-Payload capacity of Steganographyrepresent more information that can be disappear and retrievesuccessfully. By comparing Watermarking, need to embedonly a small amount of copyright information, Steganographyaims at hidden communication and therefore requiressufficient embedding capacity. By using this, small amount ofdata could be wrapped by human eyes.

Robustness:-Robustness of Steganography representcommunication of stego image by trusted systems. It measuresthe ability of the steganographic technique to carry on theattempt of cut out the hidden information. Such attemptsinclude, image manipulation like cropping or rotating, datacompression, and image filtering.

Techniques Invisibility Payloadcapacity

Robustness

SpatialDomainTechnique

High High Low

TransformDomainTechnique

High High Low

DistortionMethodTechnique

Low Low Low

SpreadSpectrumMethod

High Medium High

MaskingandFiltering

Low High Medium

Table.1: Comparison of Digital Image SteganographyTechniques

V. RESULT ANALYSISAbove Table shows the comparison of Image

Steganography techniques with parameters like, Invisibility,Payload Capacity and Robustness. All technique Comparisonsatisfies the Fundamentals are High, Medium and Low. AHigh level means that the techniques completely satisfy therequirement. A Low level means the technique has weaknessin this requirement. A medium level indicate that it is neithercomplete nor weakness.

In all above technique Spatial domain technique isbest technique for digital image Steganography. In the LSBtechnique, the LSB of the pixels is replaced by the message tobe sent, this has the effect of distributing bits evenly. Itsinvisibility as well as robustness is high.If requirement forImage Steganographic Technique is high capacity thenproposed Image technique could be used for this purpose.

CONCLUSION

Albeit, only one of the main Digital imageSteganography technique were discussed in this paper, one cansee that there exist a large selection of approaches to takecover information in images. The entire image file formatshave different method of hiding message with different strongand weak point. The consequences are presented in terms ofclassification that focuses on five Image techniques for hidinginformation in image file. Those techniques modifying theimage in Spatial Domain Method, Spread SpectrumTechnique, Transform Domain Technique, DistortionTechnique and Masking and Filtering Technique. Eachtechnique tries to satisfy the three factor of Steganographydesign i.e. invisibility, payload capacity and robustness. FromTABLE.1, one can deduce that while one may lack in payloadcapacity, another may lack in robustness. For example: LSBtechnique in a spatial domain has a high payload capacity, butthey often fail to prevent statical attack. It is more hidingcapacity but less robust than other techniques, so, the spatialdomain technique is one of the most important techniques forproposed digital image technique.


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Robustness


High High Low


High High Low


Low Low Low


High Medium High

MaskingandFiltering

Low High Medium





CONCLUSION



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Robustness


High High Low


High High Low


Low Low Low


High Medium High

MaskingandFiltering

Low High Medium





CONCLUSION



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REFERENCES

[1] Mr. Falesh M. Shelke1, Miss. Ashwini A. Dongre2, Mr. Pravin D. Soni3(2feb 2014)“Comparison of different techniques for Steganography inimages” In proceeding IJAIEM, vol 3, issue2, ISSN 2319 – 4847.[2] C.P.Sumathi1, T.Santanam2 and G.Umamaheswari.” A Study of VariousSteganographic Techniques Used for Information Hiding” In proceeding(IJCSES) Vol.4, No.6, December 2013.[3] MehdiHussain and MureedHussain” A Survey of Image SteganographyTechniques” International Journal of Advanced Science and Technology Vol.54, May, 2013 113[4]BablooSaha and ShuchiSharma”Steganographic Techniques of DataHiding using Digital Images”.Defence Science Journal, Vol. 62, No. 1,January 2012, pp. 11-18, DOI: 10.14429/dsj.62.14362012.[5] H. S. Majunatha Reddy and K. B. Raja, (2009) High capacity and securitysteganography using discrete wavelet transform. International Journal ofComputer Science and Security. pp. 462-472.[6] S. C. Katzenbeisser. Principles of Steganography.in Information HidingTechniques for Steganography and Digital Watermarking”, S. Katzenbeisserand F. Petitcolas, Ed. London: Artech House, (2000), pp. 43-78[7] P. Kruus, C. Scace, M. Heyman, and M. Mundy., A survey ofsteganography techniques for image files .Advanced Security ResearchJournal.[On line], 5(1), (2003), pp. 41-52.[8] JasleenKour, DeepankarVerma” Steganography Techniques” inproceeding Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-3, Issue-5)[9] Handel, T. &Sandford, M., “Hiding data in the OSI network model”,Proceedings of the 1st International Workshop on Information Hiding, June(1996).[10] N. Johnson and S. Jajodia, “Exploring steganography: seeing theunseen”, IEEE Computer, pp. 26-34, February (1998).

AUTHOR’S PROFILE

ShraddhaD. NimkaleM.Sc. computer scienceP.G. department of computer science and technology,H.V.P.M an autonomus college, Amravati

Priyanka A. SawarkarM.Sc. computer scienceP.G. department of computer science and technology,H.V.P.M an autonomus college Amravati.

Vilas S. BelsareAssistant Prof. P.G. Department of computer science&Technology.D.C.P.E. H.V.P.M.Amravati.Qualification M.C.A.Experience: 26 yr.


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Study and Comparison of Digital Image Steganography · Study and Comparison of Digital Image Steganography ... The steganographic methods are classified in to ... protocol steganography.

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