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A NOVEL STEGANOGRAPHIC APPROACH: EMBEDDING SECRET TEXT IN VIDEO K. Neeraja,Assistant Professor, Department of Computer Science & Engineering, JNTUH college of Engineering, Hyderabad. [email protected] August 6, 2018 Abstract Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the internet. For hiding secret information in images, there exists a large variety of Steganographic techniques some are more complex than others and all of them have respective strong and weak points. The proposed method implements a new method for the real time hiding of information used in compressed video bit stream. The new criteria employing statistical invisibility of continuous frames is used to adjust the embedding strategy and capacity, which increases the security of proposed algorithm. Few applications may require absolute invisibility of the secret information, while others require a larger secret message to be hidden. The proposed work tends to give an overview of video steganography, for a more secure 1 International Journal of Pure and Applied Mathematics Volume 120 No. 6 2018, 11855-11877 ISSN: 1314-3395 (on-line version) url: http://www.acadpubl.eu/hub/ Special Issue http://www.acadpubl.eu/hub/ 11855
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Page 1: A NOVEL STEGANOGRAPHIC APPROACH: EMBEDDING SECRET TEXT … · A NOVEL STEGANOGRAPHIC APPROACH: EMBEDDING SECRET TEXT IN VIDEO K. Neeraja,Assistant Professor, Department of Computer

A NOVEL STEGANOGRAPHICAPPROACH: EMBEDDING SECRET

TEXT IN VIDEO

K. Neeraja,Assistant Professor,Department of Computer Science & Engineering,

JNTUH college of Engineering, [email protected]

August 6, 2018

Abstract

Steganography is the art of hiding the fact thatcommunication is taking place, by hiding information inother information. Many different carrier file formats canbe used, but digital images are the most popular becauseof their frequency on the internet. For hiding secretinformation in images, there exists a large variety ofSteganographic techniques some are more complex thanothers and all of them have respective strong and weakpoints.

The proposed method implements a new method for thereal time hiding of information used in compressed videobit stream. The new criteria employing statisticalinvisibility of continuous frames is used to adjust theembedding strategy and capacity, which increases thesecurity of proposed algorithm.

Few applications may require absolute invisibility of thesecret information, while others require a larger secretmessage to be hidden. The proposed work tends to give anoverview of video steganography, for a more secure

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approach, the project encrypts the message using secretkey and then send it to the receiver. The receiver thendecrypts the message to get thee original one. MoreoverPSNR of cover image with stegno image shows the betterresults in comparison with other existing steganographyapproaches

Keywords:Steganography, PSNR.

1 INTRODUCTION

One of the reasons that intruders can be successful is the most ofthe information they acquire from a system is in a form that theycan read and comprehend. Intruders may reveal the informationto others, modify it to misrepresent an individual or organization,or use it to launch an attack. One solution to this problem is,through the use of steganography. Steganography is a technique ofhiding information in digital media. In contrast to cryptography,it is not to keep others from knowing the hidden information butit is to keep others from thinking that the information even exists.

Steganography become more important as more people join thecyberspace revolution. Steganography is the art of concealinginformation in ways that prevents the detection of hiddenmessages. Steganography include an array of secretcommunication methods that hide the message from being seen ordiscovered.

Due to advances in ICT, most of information is keptelectronically. Consequently, the security of information hasbecome a fundamental issue. Besides cryptography, steganographycan be employed to secure information. In cryptography, themessage or encrypted message is embedded in a digital host beforepassing it through the network, thus the existence of the messageis unknown. Besides hiding data for confidentiality, this approachof information hiding can be extended to copyright protection fordigital media: audio, video and images.

The growing possibilities of modern communications need thespecial means of security especially on computer network. The

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network security is becoming more important as the number ofdata being exchanged on the internet increases. Therefore, theconfidentiality and data integrity are requires to protect againstunauthorized access and use. This has resulted in an explosivegrowth of the field of information hiding

Information hiding is an emerging research area, whichencompasses applications such as copyright protection for digitalmedia, watermarking, fingerprinting, and steganography.

In watermarking applications, the message contains informationsuch as owner identification and a digital time stamp, whichusually applied for copyright protection.

Fingerprint, the owner of the data set embeds a serial numberthat uniquely identifies the user of the data set. This adds tocopyright information to makes it possible to trace anyunauthorized use of the data set back to the user.

2 LITERATURE SURVEY

Steganography:

The objective of steganography is to hide a secret message withina cover-media in such a way that others cannot discern thepresence of the hidden message. Technically in simple words”steganography means hiding one piece of data within another”.

Modern steganography uses the opportunity of hiding informationinto digital multimedia files and also at the network packet level.Hiding information into a media requires following elements [2].The cover media(C) that will hold the hidden data. The secretmessage (M), may be plain text, cipher text or any type of data.The stego function (Fe) and its inverse (Fe-1) .An optionalstego-key (K) or password may be used to hide and unhide themessage.

The stego function operates over cover media and the message (to

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be hidden) along with a stego-key (optionally) to produce a stegomedia (S). The schematic of Steganographic operation is shownbelow.

Fig 2.1: The Steganographic operation

Steganography and Cryptography are great partners in spite offunctional difference. It is common practice to use cryptographywith steganography.

2.1 Modern Techniques of Steganography

The common modern technique of steganography exploits theproperty of the media itself to convey a message.

A. Plaintext steganographyB. Still imagery steganographyC. Modification of LSB of a cover image in ’bitmap’ formatD. Transformation techniqueE. ENCODING

3 RELATED WORK

Throughout history Steganography has been used to secretlycommunicate information between people.

Some examples of use of Steganography is past times are:

1. During World War 2 invisible ink was used to writeinformation on pieces of paper so that the paper appearedto the average person as just being blank pieces of paper.

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Liquids such as milk, vinegar and fruit juices were used,because when each one of these substances are heated theydarken and become visible to the human eye.

2. In Ancient Greece they used to select messengers and shavetheir head, they would then write a message on their head.Once the message had been written the hair was allowed togrow back. After the hair grew back the messenger was sentto deliver the message, the recipient would shave off themessengers hair to see the secrete message.

Another method used in Greece was where someone wouldpeel wax off a tablet that was

The former consists of linguistic or language forms of hiddenwriting. The later, such as invisible ink, try of hide messagesphysically. One disadvantage of linguistic steganography is thatusers must equip themselves to have a good knowledge oflinguistry. In recent years, everything is trending towarddigitization. And with the development of the internet technology,digital media can be transmitted conveniently over the network.Therefore, messages can be secretly carried by digital media byusing the steganography techniques, and then be transmittedthrough the internet rapidly.

Steganography is the art of hiding the fact that communication istaking place, by hiding information in other information. Manydifferent carrier file formats can be used, but digital images arethe most popular because of their frequency on the internet. Forhiding secret information in images, there exists a large variety ofsteganography techniques some are more complex than others andall of them have respective strong and weak points.

So I prepare this application, to make the information hiding invideo more simple and user friendly.

In this work I developed a stego machine to develop aSteganographic application to hide data containing text in acomputer video file and to retrieve the hidden information. Thiscan be designed by embedding text file in a video file in such a

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way that the video does not lose its functionality using LeastSignificant Bit (LSB) modification method. This method appliesimperceptible modifications. This proposed method strives forhigh security to an eavesdroppers inability to detect hiddeninformation.

Figure 3.1 Model of steganography

3.1 Steganography Techniques

Over the past few years, numerous steganography techniques thatembed hidden messages in multimedia objects have beenproposed. There have been many techniques for hidinginformation or messages in images in such a manner thatalteration made to the image is perceptually indiscernible.Commonly approaches are include LSB, Masking and filtering andTransform techniques.

Least significant bit (LSB) insertion is a simple approach to

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embedding information in image file. The simplest steganographytechniques embed the bits of the message directly into leastsignificant bit plane of the cover-image in a deterministicsequence. Modulating the least significant bit does not result inhuman perceptible difference because the amplitude of the changeis small. In this technique, the embedding capacity can beincreased by using two or more least significant bits. Theadvantage of LSB-based method is easy to implement and highmessage pay-load.

Although LSB hides the message in such way that the humans donot perceive it, it is still possible for the opponent to retrieve themessage due to the simplicity of the technique. Therefore,malicious people can easily try to extract the message from thebeginning of the image if they are suspicious that there existssecret information that was embedded in the image.

Therefore, a system named Secure Information Hiding System(SIHS) is proposed to improve the LSB scheme. It overcomes thesequence-mapping problem by embedding the massage into a setof random pixels, which are scattered on the cover-image.

4 SYSTEM DESIGN

Software design is a process through which the requirements aretranslated into a representation of a s/w. One of the softwarerequirements have been analyzed and specified, the s/w designinvolves three technical activities: design, coding generation andtesting. The design of the system is in modular form i.e., the s/wis logically partitioned into components that perform specificfunctions and sub functions.

The design phase leads to modules that exhibit independentfunctional characteristics. It even leads to interfaces that reducethe complexity of the connections between modules and with theexternal environment. The design phase is of main importancebecause in this activity, decisions ultimately affect the success ofsoftware implementation and maintenance.

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Fig 4.1 Architecture of video steganography

5 MODULES

5.1 Frame Conversion

For converting the video in to frames we are using a specialfunction in matlab called frame conversion function. The need ofconverting the video in to frames we can easily embed the data into frames then embed in to video.

Frame conversion Callback(hObject, eventdata, handles)

5.2 Data Embedding:

Data embedding is a new Steganographic method for combiningdigital information sets. Information is embedded into, andextracted from, TrueColor or color-pallet images in Microsoftbitmap (BMP) format. Hiding data in the noise component of ahost, by means of an algorithm that modifies or replaces the noisebits, is termed ‘steganography.’ Data embedding differs markedlyfrom conventional steganography, because it uses the noisecomponent of the host to insert information with few or nomodifications to the host data values or their statisticalproperties. Consequently, the entropy of the host data is affected

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little by using data embedding to add information. The dataembedding method applies to host data compressed withtransform, or ‘lossy’ compression algorithms, as the proposedproject work is based on discrete cosine transform and waveletfunctions.

5.3 Compression

Data compression, source coding, or bit-rate reduction involvesencoding information using fewer bits than the originalrepresentation. Compression can be either lossy or lossless.Lossless compression reduces bits by identifying and eliminatingstatistical redundancy. No information is lost in losslesscompression. Lossy compression reduces bits by identifyingmarginally important information and removing it.

Video Compression Video compression uses modern codingtechniques to reduce redundancy in video data. Most videocompression algorithms and codecs combine spatial imagecompression and temporal motion compensation. The proposedvideo compression algorithms use lossy compression. Largeamounts of data may be eliminated while being perceptuallyindistinguishable.

These pixel groups or blocks of pixels are compared from oneframe to the next and the video compression codec sends only thedifferences within those blocks. In areas of video with moremotion, the compression must encode more data to keep up withthe larger number of pixels that are changing. Commonly duringexplosions, flames, flocks of animals, and in some panning shots,the high-frequency detail leads to quality decreases or to increasesin the variable bitrate.

The following techniques are employed to achieve desirablereductions in image data:

• Reduce color gradation within the image

• Reduce the color resolution with respect to the prevailing lightintensity

• Remove small, invisible parts, of the picture

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• Compare adjacent images and remove details that areunchanged between two images

5.4 DCT Transformation

5.4.1 The Discrete Cosine Transform (DCT)

The discrete cosine transform (DCT) helps separate the image intoparts (or spectral sub-bands) of differing importance (with respectto the image’s visual quality). The DCT is similar to the discreteFourier transform: it transforms a signal or image from the spatialdomain to the frequency domain (Fig 4.1)

Fig 5.1 DCT

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Fig 5.2: DCT Encoder Decoder

5.5 Quantization

After output from the FDCT, each of the 64 DCT coefficients isuniformly quantized in conjunction with a 64-elementQuantization Table, which must be specified by the application(or user) as an input to the encoder. Each element can be anyinteger value from 1 to 255, which specifies the step size of thequantizer for its corresponding DCT coefficient. The purpose ofquantization is to achieve further compression by representingDCT coefficients with no greater precision than is necessary toachieve the desired image quality. Stated another way, the goal of

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this processing step is to discard information which is not visuallysignificant. Quantization is a many-to-one mapping, and thereforeis fundamentally lossy. It is the principal source of lossiness inDCT-based encoders. Quantization is defined as division of eachDCT coefficient by its corresponding quantizer step size, followedby rounding to the nearest integer:

FΩ = IntegerRound(

F (u,v)Q(u,)

)

This output value is normalized by the quantizer step size.De-quantization is the inverse function, which in this case meanssimply that the normalization is removed by multiplying by thestep size, which returns the result to a representation appropriatefor input to the IDCT:

FΩ(u, v) = FΩ(u, v) ∗Q(u, v)

To compress the image as much as possible without visibleartifacts, each step size ideally should be chosen as the perceptualthreshold or just noticeable difference for the visual contributionof its corresponding cosine basis function. These thresholds arealso functions of the source image characteristics, displaycharacteristics and viewing distance.

5.5.1 DC Coding and Zig-Zag Sequence

After quantization, the DC coefficient is treated separately fromthe 63 AC coefficients. The DC

Coefficient is a measure of the average value of the 64 imagesamples. Because there is usually strong correlation between theDC coefficients of adjacent 8x8 blocks, the quantized DCcoefficient is encoded as the difference from the DC term of theprevious block in the encoding order (defined in the following), asshown in Figure 4.4. This special treatment is worthwhile, as DCcoefficients frequently contain a significant fraction of the totalimage energy.

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Fig 5.3: Zig-Zag Sequence

5.5.2 Retrieving the data

The receiver receives the data after frame conversion done to thevideo received from the sender after embedding the data,

5.5.3 Stego Module (Reverse Process)

For Stego Module the following steps are considered for retrievingthe cipher text ( Figure4.7):

• Take DCT of the Original Image.

• Take DCT of the Stego Image.

• Take difference of DCT coefficients.

• Retrieve bits of the hidden seven alphabets from LSB of theDCT.

• Construct the distorted seven alphabets.

• Unscrambled the distorted seven alphabets using Key 2.

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• Retrieve the original seven alphabets.

Fig 5.4: Encoding and Decoding

5.5.4 Security Module(Reverse Process)

For Security Module the following steps are considered for retrievingthe cipher text

• Club the seven characters with the alphabets of Key 4.

• Using Key 3 and Key 4 reconstruct the cipher text fromalphabets and digits.

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Fig 5.5: Security Module (Reverse Process)

6 RESULTS

Fig 6.1: Main screen

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Fig 6.2: Encoding Process

Fig 6.3: Encoded matrix values

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Fig 6.4: Frame matrix for insertion of text

Fig 6.5: Cipher text

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Fig 6.6: Decoding

Fig 6.7: Reconstruction of output

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Fig 6.8:Folder View

7 CONCLUSIONS AND FUTURE

WORK

In the present work we try to embed some secret message insideany cover file in encrypted form so that no one will be able toextract actual secret message. Here we use the standardSteganographic method i.e. changing LSB bits of the cover file.This method is essentially stream cipher method and it may takehuge amount of time if the files size is large and the encryptionnumber is also large. The merit of this method is that if change inthe key text little bit then the whole encryption and decryptionprocess will change. This method may most suitable for watermarking. In the proposed video steganography method it isfurther secured by compress the secret message first and thenencrypt it and then finally embed inside the cover file. VideoSteganography, especially combined with cryptography, is apowerful tool which enables people to communicate withoutpossible eavesdroppers even knowing there is a form ofcommunication in the first place. The methods used in the scienceof steganography have advanced a lot over the past centuries,especially with the rise of the computer era.

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In future instead of generating secret message using .txtdocument, messages can be generated by the combination of thefollowing types like,

.JPG :- .JPG,.BMP,.TXT,.WAV,.MP3,. XLS,,.PPT, .EXE,.COM

.DOC :- .TXT

.WAV :- .BMP,.JPG,.TXT,.DOC

.AVI :- .TXT,.WAV,.JPEG

.PDF :- .TXT

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[1] Steganography and steganalysis-Robert Krenn, InternetPublication, March 2004

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[20] Pennebaker, W.B., Mitchell, J.L., et. al. Arithmetic codingarticles. IBM J. Res. Dev., vol. 2, no. 6 (Nov. 1988), pp. 717-774.

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