Using LSB Steganography Technique and 256 bits ...

Volume 7, Issue 5, May 2017

ISSN: 2277 128X

International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com

Using LSB Steganography Technique and 256 bits Key Length AES Algorithm for High Secured Information Hiding Eric Gyamfi Department of Electrical and Electronic Sunyani Technical University Sunyani, Ghana

Isaac Kofi Nti Department of Computer Science Sunyani Technical University Sunyani, Ghana

Justice Aning Department of Computer Science Sunyani Technical University Sunyani, Ghana

Abstract— Networking of computer and information communication and technology (ICT) devices, gives a better and an efficient medium for information and data shearing around the globe, among people and organisations. The ever increasing demand of information shearing and data communication over computer networks, has paved way for attackers to attack data in transient and stored data. This has made the security of data become a major problem. Cryptography and Steganography are two dissimilar information hidden techniques. Whiles cryptography conceals the content of the message, steganography conceals an information within other digital media such as image, audio, video etc. This study propose a high-volume information concealment methodology by blending Cryptography and Steganography. With this approach an information (message) is encrypted first using a 256 bits Key Length AES Algorithm and the output result (encrypted message) is concealed within an image employing LSB insertion methodology. Employing this two techniques give more and better security to the concealed information and will satisfy the requirement such as security, capacity and robustness for safer and secure transmission of information over an exposed channel. The Peak Signal to Noise Ratio (PSNR) and Mean square error (MSE) were computed for a comparative analysis to make evident the effectiveness of the proposed methodology, also images performance factors such as Mean, Entropy and Standard Deviation were used to ascertain the data hidden techniques of the framework. The stego-images are verified by transmitting them and the concealed information are effectively pull out by the receiver. Keywords— Steganography, Least Significant Bit, encryption, Cryptography, plaintext, decryption, transposition cipher, Peak Signal to Noise Ratio, Mean square error. I. INTRODUCTION Steganography is a word originated from the Greek language which means concealed or covered writing, and it’s a section of information security, which deals with the hiding of access to an important information existence from unauthorised person [1], [2]. Same as cryptography, steganography aids in safeguarding vital information, each method of protecting the data or information is quite different from the other. In Cryptography the information (plaintext or meaningful text) is transformed into an unintelligent or scrambled text such no one can understand the cypher text apart from the intended received that has the key to decipher the text [3]. Whiles steganography hides the data in an innocent or clear media, in a way that intruders cannot notice the existence of the data [4], [5], [2]. Some of the innocent media used for steganography are signals, text, images and videos etc. The aim of steganography is to conceal the presence of a message and to form a covert conduit. Normally the message is concealed in another object and then transmitted or saved. If the presence of the concealed message is seen, the objective of steganography is crushed.

Cover

Stego Image

Concealing Algorithm

Infomation Pulling-Out Algorithm

Information Figure 1 Basic Steps in Steganography Figure 1 shows the basic steps in steganography, which has an information (plaintext), a cover image, concealing algorithm, stego-image and an extraction or pulling-out algorithm. The cover image is a clear image in which the message bit is hide, different image format such as gif, jpg and bmp etc. can be used. Most research work on image steganography employs bit map Image file format due to its lossless compression ability [6], [2]. To guarantee information security and also warrants that data does not go to unintended target or end, the idea of data or information hiding came up to safeguard a piece of data or information. © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681

Steganography

Image

Transform

Text

Compression

Protocol

Video/Audio

Spatial

Figure 2 Classification of Steganography Techniques Figure 2, shows the classification steganography, Text Steganography have three basic modules that square measure as shown in figure 2 [7], Linguistic methods: Serious of linguistic analysis makes this an interesting medium for stenographic data concealment. Format-based methods: Conceal the stenographic text inside the existing cover text by dynamical data like insertion of areas or non-displayed characters, cautious errors tinny throughout the text and resizing of fonts [7]. Random and applied arithmetic generation method: in this approach do not make any comparison with a well-known plaintext, stenographers normally resort to producing their own cover texts [7]. Image steganography is usually clustered into two types thus transform domain image steganography and spatial domain image steganography. Image steganography where original pixel values are used for concealing the secret information is known as spatial domain image steganography, and where transformed pixels are employed for hiding the secret information is known as transform domain image steganography [2], [8]. Every image steganography has three main goals namely; high imperceptibility (security), high payload capacity and robustness. Imperceptibility stands how the secret information or date is hidden such that an authorised person or intruder cannot detect the existence of secret information in the cover image and this is measured using peak signal to noise ratio (PSNR). The higher the PSNR values the more difficult it is for an intruder to see the existence of the secret date. The payload capacity determines the number of bits employed per pixel for concealing the secret data. Finally, the ability of the cover image (original image) to resist manipulations or attacks without drawing any attention that a change has taken place is known as robustness [2], [5], [8]. Numerous image steganography methods has been presented, but the most commonness method used is the least significant bits (LSB). The LSB matching algorithm was presented by (Ker et al., 2004) cited by [9], in this techniques the LSB of the image pixel are used for secret message bit embedding, thus directly replacing the LSBs of pixels in the cover or original image with secret bits to produce the stego-image [2], [9], [10], [11]. LSB replacement algorithm is the modest scheme to hide message or information in a host image. It substitutes the least significant bit (LSB) of each pixel with the encrypted message bit stream. Because only the LSB of pixels is changed, it is visually invisible by human. The ability of the algorithm is 1 bit per pixel. The LSB steganography technique has a high imperceptibility, but it simplicity has made it prone to attacks such as difference image histogram [2], [12], sample pair analysis [13] and blind detection algorithm [14]. In a quest to provide more security to the above mentioned attacks a randomization techniques was added and a total with the name “Hide and seek” was introduce [15], but still Laplace formula attacked this tool with easy. Steganography and Cryptography can be parallel to provide more data security, thus a steganography system can also make use of cryptographic data security. Implementing cryptography can protect the message or information but cannot hide its existence [10], [16]. While cryptography providing security for the information (plaintext), steganography pay attention to the degree of hiddenness of the information in the cover image [17]. In a case where the presence of the hidden information is detected or suspected, the purpose of steganography is partly defeated [10], [18]. Thus steganography’s strength can be further increase and intensified by adding cryptography. Concealment of information using LSB technique only is not highly secure [5]. In support with [5], [18], this study seeks to propose a system with additional security topographies where an important piece of message (plaintext) can be concealed by merging two elementary information hiding techniques, thus LSB Steganography technique and 256 bits Key Length AES algorithm. Combining this two techniques will ensure that, the data is secured from unauthorized person, and fortify the requirements such as security, capacity and robustness for secure data in transmission over an exposed channel. Again even if an unauthorised person or attacker is successful in defeating the steganography technique to get access to the messes he/she has to decipher the encrypted message. II. LSB IMAGE STEGANOGRAPHY TECHNIQUES IN SPATIAL DOMAIN Two researchers, namely; Sushil Jajodia and Neil F. Johnson in the year 2000, elaborated on three well-known approaches for data, message or information hidden in digital images [9]. These approaches were; © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681 i. Masking and filtering ii. LSB insertion iii. Algorithmic transformations. In the year 2003 Kevin Curran and Karen Bailey also did an analyses of 7 diverse image based steganography procedures, and methodologies were;  Stego1bit  Stego2bits  Stego3bits  Stego4bits  Stego Colour Cycle  StegoPRNG  StegoFridrich. Normally, Steganography methods are categorised into LSB matching, LSB substitution, Adaptive LSB and PixelValue Differencing (PVD), Component based LSB Edge detection filter based, and Texture based [9]. III. IMAGE STEGANOGRAPHY USING LSB TECHNIQUES The most commonness digital media used for steganography is an image, because of it abundancy in redundant data and this makes it possible to hide messages, information or data within image file [19]. In the computer environs an image is collection of numbers that made-up dissimilar light intensities in diverse areas of the image. The numeric arrangement forms a grid and every points are known as pixels and this pixels constitute the raster data of the image. Image steganography is all about the exploitation of the human visual system (HVS) limits [10]. Viewing any specific colour closely, one can observed that single or distinct digit change to the contribution level is unnoticeable to the eye of humans, for example a pixel with a unique value (255, 255, 0) is indiscernible from (254, 255, 0)) in RGB colour picture [10]. Data associated with images mostly are too large for internet data transmission, hence some techniques and methods are employed to reduce the image data to reasonable size in order for fast transmission and viewing on the internet. The technique is known as compression and its uses mathematical modules for the reduction of the image data, this method plays a very key starring role in image based steganography techniques. Substitution techniques popularly known as spatial domain steganography techniques, be made up of simple techniques that builds a secret channel in the parts of the cover image in which changes are likely to be unnoticeable to the HVS. One simple approaches to do so is to hide information in the LSB of the image data [5]. The LSB in an image is considered as random noise and hence when substitutes do not pose any change on the image. The LSB steganography techniques is the most common use inserting algorithm in image steganography due to it easiness, but yet offers a remarkably effectiveness [5], [20]. The changing the LSB in a particular layer within the image file the secret message is hidden. The concealing procedure of LSB steganography technique as shown in the following equation: Where mk, xk and yk are the kth message bit and the kth selected pixel value before and after embedding, respectively. Assume {Pm (x = 0), P (x = 1)} denote the distribution of the LSBs of the cover image, whiles {Pm (m = 0), P (m = 1)} denote the distribution of the secret binary message bits. Additional security must be given to the message by compressing or encrypting it before being concealed just to safeguard its secrecy. In accordance to this, the sharing of the message may be anticipated to equal an averaged distribution, such that

An image will have a noticeable impact on the colour if the most significant bits (MSBs) is altered, but altering the LSBs is unnoticeable to the human eye. The format of image employed in LSB are lossless and data can be easy manipulated and recovered [21]. With lossless data compression the original date can be retrieved and reconstructed from the compressed data using compression algorithms. The lossless compression is done to maximise the concealment capacity of the cover image, thus compression the data allows for more data to be hidden. Digital image steganography makes use of the weakness in the HVS, which has a low sensitivity in pattern changes and luminance. Using the LSB technique for information concealment attains both inconspicuousness and reasonably high storage payload [5]. The LSBs techniques do not result in image distortion when used for data hidden and also the subsequent stego-image looks alike to the cover-image [22]. This paper employs the LSB methodology of steganography and also do a comparison the data concealment at one LSB and two LSB positions and assessed the performance parameters like Mean, Standard Deviation and Entropy etc. The data is encrypted using Advance Encryption Standard Algorithm. IV. PROPOSED METHOD To improve on the amount of data that can be hidden in image steganography and also enhancing the unnoticeability of the stegoimage to human vision, this paper propose a framework for concealing larger data volumes in © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681 images by merging AES 128 key length cryptography and LSB steganography techniques with no data loss and providing a solution to the problem of unauthorized data access. Steganography may also be applied to cryptographic data to provide more data security. In this method, the message (the secret) is firstly encrypted using AES method and then concealed the encrypted (secret) message within a cover image by means of LSB embedding method as shown in figure 3. Combining this two techniques will ensure that the data is secured from unauthorized person, and stratify the requirements such as security, capacity and robustness for secure data in transmission over an exposed channel. Message

AES Encryption

Encrypted Message

Stego Image

Hiding Algorithm

Pulling-Out Algorithm

Encrypted Message

Decipher Message

Message

Figure 3 Proposed Method V. ENCRYPTION Advance Standard Encryption is a 128 bit block cipher that takes key lengths of 128, 192, and 256 bits. The number of rounds required (i.e., linear and non-linear transformations), depend on the key size [3]. Table 1 shows the FIPS 197 conformant Key-Block-Round combinations.

AES - 128 AES – 192 AES - 256

Table 1 Key-Block Round Combination Key Length Block Size Number of Rounds (Nr) (Nk Words) (Nb Words) 4 4 10 6 4 12 8 4 14

During the cipher and decipher process, a round function that is made-up-of four dissimilar byte-oriented transformations: 1) is use, byte substitution using a substitution table (S-box), 2) shifting rows of the State array by different offsets, 3) mixing the data within each column of the State array, and 4) adding a Round Key to the State. VI. MESSAGE CONCEALMENT PROCEDURE After encrypting the message which is to be concealed in an image, the message is transformed into ASCII equivalent form for onwards conversion to binary data format. For say if “t” is encrypted character its equivalent is 116 in ASCII and 1110100 for binary equivalent, then 1110100 is embedded in the image using the LSB technique.  Iterate via the pixels of the image. Get the RGB values and separate each in a separate integer in every iteration.  For each of R, G, and B, make the LSB equals to 0. These bits is used in concealing the characters.  Fetch the current character and convert it to integer. Then hide its 8 bits in R1, G1, B1, R2, G2, B2, R3, G3, where the numbers refer to the numbers of the pixels. In every LSB of these elements (from R1 to G3), conceal the bits of the character consecutively.  After processing the 8 bits of the character, jump to the next character, and reiterate the process until the whole text is dealt with.  The encrypted message can be concealed in a small portion of the image according to the length of that message. Therefore, there must be an indicator to indicate the end of message. The indicator is basically 8 sequential zeros and this is used in the message extraction from the image phase. VII. MESSAGE EXTRACTION PHASE The inverse of the message concealment algorithm in the extraction algorithm. The stego-image is sent to the steganalysis algorithm when the recipient received the stego-image to extracted the message and then decipher the message. In extracting the encrypted data, message or information, the stego-image file is opened and the RGB colour of each pixel is read. The LSBs of every single pixel of stego-image is extracted. The information extracted from the stego-image © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681 is the encrypted form of the original information, the retrieved information is then decrypted using AES decryption algorithm. VIII. RESULTS AND DISCUSSIONS The proposed methodology gives a high rate of data hiding and provides higher security level. Matlab was used for implementing the proposed framework and the following sections gives the in details the observations. Theree different images of size ranging from 34 KB to 48 KB were used for the experiment and in each image a secret message was successfully concealed inn. Figure 4, 5,6,7,8 and 9 shows the various images before and after steganography. There is no difference in the original image and the stego-image after performing LSB concealment. The modification in the original image (cover image) is not noticeable on the stego-image to the human eye. There is no change in the size of the stego-image compared to the original image and the secret information hidden in the stego-image were successfully retrieved. The efficiency of the proposed framework was determined in relation to similarity Mean Square Error (MSE) and PSNR (peak signal to noise ratio) given by equation (3) and (4)

Where mean square error (MSE) is the standard used to quantify the difference between the cover image I and the stego- image II. With the image have an M * N size.

Figure 4 Flower (A) before Steganography

Figure 5 Flower (AI) After Steganography (stego-image)

Figure 6 Flower (B) before Steganography © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681

Figure 7 Flower (BI) After Steganography (stego-image)

Figure 8 Flower (C) before Steganography

Figure 9 Flower (CI) After Steganography (stego-image)

Cover Image A (40 KB) B (36 KB) C (45KB)

Table 2 MSE and PSNR values for the Original and Stego-images Stego Image Amount of data MSE % PSNR (dB) embedded AI (40 KB) 607 Bytes 0.62 39.02 I B (36 KB) 607 Bytes 0.41 48.46 CI (45KB) 607 Bytes 0.57 49.68

Amount of data extracted 607 Bytes 607 Bytes 607 Bytes

PEAK SIGNAL TO NOISE RATIO (PSNR) ASSESSMENT In a normal condition, an increase in payload produces a corresponding increase in MSE and MSE increase affects the PSNR inversely. It was realised that MSE reduction produces PSNR rise and vice-versa. The PSNR values were expressed in logarithmic scale in decibels (dB). From table 2 stego-image AI has a PSNR of 39.02 indicating a fairly low quality, thus distortion causes by the concealment is obvious. Whiles stego-image BI and CI has PSNR of 48.46 and 49.68 respectively, indication of a high and quality stego-image as proposed by [23, 5] that a good stego-image should have a PSNR of 40 dB and above. The result as shown in table 2 reveals that image concealment algorithm introduced high PSNR and less perceptual distortion. The distortion introduced after the concealment of the information in the cover-image was ascertain by observing the PSNR after concealment for stego-images AI, BI and CI and it is seen that the PSNR is constantly above 40 dB for stegoimages BI and CI as seen in table 2 . This shows that the quality the information concealed in the cover image is hardly to be seen by the human eye. © 2017, IJARCSSE All Rights Reserved

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Gyamfi et al., International Journal of Advanced Research in Computer Science and Software Engineering 7(5), May- 2017, pp. 674-681 MEAN, ENTROPY AND STANDARD DEVIATION ASSESSMENT The proposed algorithm was also tested in contrast to image factors like Mean, Entropy and Standard deviation to ascertain the impact on the image in case of replacement of bits. This was done by performing statistical distortion analysis between the stego-image and cover-image. The results are computed and summarised as shown in table 3. The Minimization of parameters dissimilarity is one of the key goals in order to get rid of statistical attacks.

Image

Mean

A B C

122.6980 225.3674 142.9557

Table 3 Image Parameters for Stego-image and Original image Before Stenography After stenograph Standard Entropy Image Mean Standard Deviation Deviation 100.2759 6.8707 AI 122.6980 100.2756 I 47.2824 5.1097 B 225.3674 47.2824 54.7812 7.6939 CI 142.9557 54.7812

Entropy 6.8707 5.1097 7.6939

Table 3, shows the measurements of mean, entropy and standard deviation between the orinal-image and the stegoimage. From the values measured, there is no significant changes in mean, entropy and standard deviation for the original and stego images. Hence the study shows the extent of change in the stego image based on image parameters is less from a cover file. The results in table 3, shows clearly that values of mean, entropy and standard deviation after the concealment are similar to the mean, entropy and standard deviation before concealment. Subsequently there is no much change in the image parameters, hence the method offers a good concealment of information and decreases the chance of the secret information being noticed. Thus it shows, an impeccably safe and sound steganographic system. Additionally, retrieving the secret information from the stego-image is deprived of any data loss problem. The key improvement in this study is that the proposed method is easy and swift and it works very fine with colour images. IX. CONCLUSIONS The conclusions arising from this study are:  The main aim of the study was to develop a system with additional security topographies where an important piece of message (plaintext) can be concealed by merging two elementary information hiding techniques, thus LSB Steganography technique and 256 bits Key Length AES algorithm. Combining this two techniques will ensure that, the data is secured from unauthorized person, and fortify the requirements such as security, capacity and robustness for secure data in transmission over an exposed channel. Again even if an unauthorised person or attacker is successful in defeating the steganography technique to get access to the messes he/she has to decipher the encrypted message.  The proposed method has the ability to conceal high data volumes with toughness against certain statistical attacks.  The proposed method is a way that the researchers wish to ascertain the condition of a good and save information concealment techniques. And not a substituted for cryptography or steganography however to complement it rather.  The concealment of data using LSB steganography makes room for high data to be concealed within a coverimage, and the proposed method appease the basic requirement for data concealment such as security, capacity and robustness.  Using steganography alone for data secrecy is not safe neither is encryption alone, but the combination of the two give a two layer of protection to the data. X. FEATURE WORKS The proposed method can be further extended and enhanced with other encryption and data concealment techniques. Feature work should look at a new techniques to give higher and efficient steganography capabilities, while ensuring higher level of resistance to statistical and visual attacks. ACKNOWLEDGMENT We express our sincere gratitude to almighty God for seeing us through and to all staff of Sunyani Technical University especially Department of Computer Science and Department of Electrical and Electronic Engineering. REFERENCES [1] D. Artz, "Digital Steganography: Hiding Data within Data," IEEE Internet Computing, vol. 5, no. 3, pp. 75-80, 2001. [2] D. Singla and M. Juneja, "New Information Hiding Technique Using Features of Image," Journal of Emerging Technologies in Web Intelligence, vol. 6, no. 2, pp. 237-242, 2014. [3] O. Nyarko- Boateng, M. Asante and I. Nti, "Implementation of Advanced Encryption Standard Algorithm with Key Length of 256 Bits for Preventing Data Loss in an Organization," International Journal of Science and Engineering Applications, vol. 6, no. 03, pp. 88-94, 2017. © 2017, IJARCSSE All Rights Reserved

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