STEGANOGRAPHY IN IMAGE SEGMENTS BY LSB SUBSTITUTION USING GENETIC ALGORITHM

e-issn 2455 1392 Volume 2 Issue 5, May 2016 pp. 475 480 Scientific Journal Impact Factor : 3.468 http://www.ijcter.com STEGANOGRAPHY IN IMAGE SEGMENTS BY LSB SUBSTITUTION USING GENETIC ALGORITHM Vinod Agnihotri 1, Anita Suman 2, Parveen Kumar 3 1,2,3 Electronics and Communication Engineering, B.C.E.T Gurdaspur143521 Abstract This paper has based on Image steganography using genetic Algorithm. This paper presents concealing the contents of secure message into the pixels of covering image. And for this purpose Genetic Algorithm has been used for hiding the contents of message into the appropriate pixel of the covering image. Another merit of this work is hiding of message contents into the LSBs of covering image which leads to the minimal change into the stego image. So it is difficult for interceptors to judge the presence of message contents into the stego image.the proposed technique is developed with MATLAB 2012 and evaluating the value of MSE and PSNR. Finally based on this technique highly secure image steganography has been achieved.all Experimental results reveals that Proposed technique offer better results as compared to existing technique. Keywords Image Encryption,LSB substitution, PSNR, Genetic Algorithm. I. INTRODUCTION In a modern era of communication the security of information contents is the major concern. And for this purpose various data hiding techniques have been developed in a couple of decades. Now a day major focus on hiding the required data with another covering data rather than providing any password based security which is the old one and can be traced out by the hackers.so initial one find more attention from few years. In a result of that various techniques like cryptography, watermarking and many other image processing based techniques have been developed and Steganography is also one of them. Steganography is the skill as well as science of protecting data in such a way that their existence can never be easily detected and also a message-transmission will happen. Classified data is encrypted in a style such that their very presence of any data is concealed. The foremost objective of steganography is to interconnect steadily in an absolutely untraceable mode and also to constrain depiction doubt towards the broadcast of a concealed data. It is not to retain some other persons from knowing the hidden information, on the other hand it is utilized to retain other peoples from thinking about the particular info even be real. Hiding Capacity plays a vital role for efficient communication. This is obtained by Steganography. The Steganography is the art of concealing the information into the other media so that the hidden information cannot detected by the human eyes. There are many different ways to keep secret information contents into an image, audio/video media, document etc. But Image Steganography has its own merits and is most popular among the others. Image steganography is characterized as the hidden implanting of information contents into advanced images. Despite the fact that steganography conceals data in any of the advanced Medium, computerized images are the most useful as bearer due to their reappearence use on the web. Since the extent of the picture record is immense, it can conceal extensive measure of data. HVS (Human Visual System) can t differentiate the typical image and the image with hidden information. The advanced images incorporates huge measure of large number of bits, pictures transformed into the most popular cover articles for steganography. Subsequently this exploration uses image as cover media. II. RELATED TECHNIQUE In recent years, there are many research technique for steganography have been proposed. Parul et al [1] presents a new approach for image steganography with the help of DWT technique. The cover @IJCTER-2016, All rights Reserved 475

image is divided into higher and lower frequency sub-bands and information contents are embedded into higher frequency sub-bands. Arnold Transformation is used to enhance the security. Deepak Singla et al [2] In this paper, they propose a LSB & DCT-based steganography method for hiding the information. Each bit of data is embedded by changing the least significant bit of low frequency DCT coefficients of cover image pixels. There are many techniques which are uses the idea of SSB-4 technique in modifying the other bits (i.e, 1st, 2nd, 3rd and/or 4th), to obtain the minimum variation between the real and the modified coefficient. Kshetrimayun Jenti [3] In this paper she purposed an image based steganography that Least Significant Bits(LSB) approach and pseudo random encoding approach on images to enhance the security of the communication. In the LSB approach, the most common idea is to replace the Least Significant Bits (LSB) of the cover image with the Bits of the messages to be hidden without effecting the property of the cover image significantly. Kamal et al [4] says that this paper uses the RSA encryption algorithm and Back Propagation Neural Network for the encryption of the message. Firstly DCT is applied to cover image, after this vector quantization matrix is achieved. After that encryption of message is done using RSA encryption algorithm and Back propagation algorithm. In the end algorithm comparison is done along with result evaluation based on PSNR and MSE parameters. Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Ell effly et al [5] Says that the combined algorithm has been implemented to enhance the security in the steganography using neural network and Levenberg-Marquardt neural network learning algorithm. It removes the disadvantage of Back propagation neural network that has the slow learning process. This proposed algorithm has been implemented on the digital images contains hidden messages. The idea is to analyze images before and after embedding to extract selective features and then build a neural network recognition model. Youssef [6] says that the proposed algorithm uses the SQL queries in the steganography using text. The message that has to hide is taken, after that it is mapped to the random text. Mapping is done using hash based search algorithm. The random word generation is equal to ASCII words. The generated words are split into two parts using select and where clause. For long select queries, a postprocessor splits them into smaller queries based on a random index. H S Manjunatha Reddy and K.B Raja [7] says that the utilization of DCT method for enhancing the High Capacity and Security Steganography. Alpha and beta parameters have been utilized for fusion of image that has been divided using DCT. Then the cover image is processed using pixel range. From the results it has been calculated that security has been achieved with good PSNR Value. Deepa et al [8] says that the steganography is usually implemented computationally, where cover Works such as text data, images, audio data, and video data are tweaked in such a way that a secret message can be embedded within them. In order to hide secret data into a cover message, the cover must contain a sufficient amount of redundant data or noise. This is because in embedding procedure Steganography actually replaces this redundant data with the secret message. Vipul Sharma and Sunny Kumar [9] says that the new steganographic algorithm that is used to hide text data inside an image. In order to enhance/ maximize the storage capacity we have used a compression algorithm that compresses or reduces the data to be embedded. The compression algorithm we have used works in a range of 1bit to 8 bits per pixel ratio. Aayushi Verma et al [12] The focus of the proposed work in this paper is on decreasing the complexity in image hiding through DWT approach while providing better security and lesser distortion in the stego image. This paper proposes the unique algorithm for embedding and extracting the secret image embedded behind the cover gray scale image. Also, the analysis of performance evaluation methods such as PSNR & MSE, gives us the experimental data for four different cases where each case uses different sizes of cover and secret image, comparing the cover image and stego image at the sender s end and embedded secret and extracted secret at the receiver s end. The hecker s attacks are then applied on the stego image and after each of the attack, the secret image is extracted from the distorted image. For better analysis, this extracted secret is compared with the expected result on the basis of PSNR and MSE. @IJCTER-2016, All rights Reserved 476

III. GENETIC ALGORITHM Genetic Algorithm is a approach which uses genetic evolution as its model to solve problems. The given problems are considered as inputs and the solutions are encoded according to a pattern. The fitness function calculate every candidate solution most of which are chosen randomly. Evolution starts from a completely random set of items and is repeated for further generations. The most suitable are picked out in every generation. Our GA aims to improve the image quality. The parameter Peak Signal to Noise Ratio (PSNR) and Mean square error(mse) can be an appropriate evaluation test. A solution to the problem are transformed into a list of parameters which are known as chromosomes. These chromosomes are usually shown as simple string of data. Initially several characteristics are generated for the prime generated randomly and the relevant proportional value is measured by the fitness function. Then the formation of the second generation of the society which is based on selection processes via genetic operators with the formerly set characteristics. Selections are devised so that to find the most appropriate component. The contents of the two chromosomes which are enter into the generation process are interacted to produce two newborn chromosomes. In this technique two of the bests are picked for intermixing to give a superb one. During each process, it is likely for a series of chromosomes to undergo mutations and generate a succeeding generation of different characteristics. Block Diagram of proposed technique: In the block diagram of this image steganography technique the text message which is to be hide is encoded into a form which can easily hide into the cover image. The cover image is also converted into its quantized form then with the help genetic algorithm change in LSB of various pixels of cover image is achieved.thus Stego image contain the text message contents but these contents are detected by the hackers.then after extraction text image is obtained from the stego image.the block diagram of this proposed technique is shown in figure1 Figure 1: Block diagram Image Steganography Planning of work Taking cover image. Conversion of RGB image in binary Giving secret message to be transmitted LSB insertion using GA Generating Stego image Extraction Result Calculations @IJCTER-2016, All rights Reserved 477

IV. EXPERIMENTAL RESULTS The proposed approach was implemented in MATLAB 2012 and images are used in Implementation are in jpg format. In this The value of MSE can be calculated with following equation: Where MSE is the Mean Squared Error of covering image (I) and stego image (K). The value of PSNR can be calculated by following equation: Where, MAXi is the maximum pixel value of the image. As in this technique of image steganography genetic algorithm is used which is based on fitness functions. So value of MSE is reduced to a greater extent,and if value of MSE is reduced, then value of PSNR could be enhanced. Lena Flower @IJCTER-2016, All rights Reserved 478

Observation Table : Image Parameter 1(PSNR) Parameter 2(MSE) Tree 65.9679 0.019901 Flowers 66.09 0.012433 Dog 69.8302 0.0024803 Mountain 69.2366 0.0025942 Lena 72.9875 0.013176 Baboon 61.6417 0.034689 Boat 65.7111 0.013591 Jet 66.5805 0.011027 Pepper 70.327 0.024313 74 72 70 68 66 64 62 60 58 56 54 Parameter (PSNR) Parameter (PSNR) Figure 2 : Graph of PSNR value @IJCTER-2016, All rights Reserved 479

0.04 0.035 0.03 0.025 0.02 0.015 0.01 0.005 0 Parameter (MSE) Parameter 2(MSE) Figure 3 : Graph of MSE value V. CONCLUSION In this paper a new approach for image steganography by LSB subsititution using Genetic Algorithm is proposed. This new technique conceal the message contents into the LSBs of appropriate pixels of covering image which are selected with the help of Genetic Algorithm and leads to the minimal change into the stego image which improve the value of PSNR and MSE to a greater extent. REFERENCES [1] Parul et al 2014 Optimized Image Steganography using Discrete Wavelet Transform (DWT) International Journal of Recent Development in Engineering and Technology [2] A.Antony Judice et al 2014 An Image High Capacity Steganographic Methods by Modified OPA Algorithm and Haar Wavelet Transform, IJCSNS International Journal of Computer Science and Network Security. [3] Po-Yueh Chen et al A DWT Based Approach for Image Steganography International Journal of applied science and engineering. [4] Deepak Singla et al 2012 Data Security Using LSB & DCT Steganography In Images International Journal Of Computational Engineering Research/ ISSN: 2250 3005 [5] Kshetrimayun Jenti2013A Sesure Image Steganog-raphy Using LSB Technique and Pseudo Random Encoding Technique [6] Kamal et al., 2014, Enhancement Key Of Cryptography And Steganography Using RSA And Neural Network, IJARCET, vol. 3, pp. 1707-1710. [7] Ell effly et al., 2013 Detecting pixel-value differencing steganography using Levenberg-Marquardt neural network, IEEE, Computational Intelligence and Data Mining (CIDM), pp. 160-165. [8] Youssef, 2012, A Generation-based Text Steganography Method using SQL Queries, IJCA, Vol. 57, pp. 27-31. [9] Babloo Sha et al, 2012, Steganographic Techniques of Data Hiding using Digital Images, DESIDOC, Vol. 62, pp. 11-18. [10] H S Manjunatha Reddy and K.B Raja, High Capacity And Security Steganography Using Discrete Wavelet Transform, International Journal of Computer Science and Security (IJCSS), Vol.3, Issue. 6, pp. 462-472. [11] Deepa et al., International Journal of Advanced Research in Computer Science and Software Engineering 3(1), Vol. 3, Issue 1, pp.54-57. [12] Vipul Sharma, Sunny Kumar, A New Approach to Hide Text in Images Using Steganography, International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 4, April 2013. [13] Elham Ghasemi, Jamshid Shanbehzadeh, and Nima Fassihi. High Capacity Image Steganography Based on Genetic Algorithm and Wavelet Transform, Intelligent Control and Innovative Computing, Lecture Notes in Electrical Engineering 110,December 2011, DOI 10.1007/978-1-4614-1695-1 30. [14] Hemalatha S1, U Dinesh Acharya2, Renuka A3, Priya R. Kamath, A Secure and High Capacity Image Steganography Technique Signal & Image Processing: An International Journal (Sipij) Vol.4, No.1, February 2013. [15] Sathya, V.; Balasubramaniyam, K.; Murali, N.; Rajakumaran, M.; Vigneswari, "Data hiding in audio signal, video signal text and JPEG images," in Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on, vol., no., pp.741-746, 30-31 March 2012. @IJCTER-2016, All rights Reserved 480