Steganography using LSB bit Substitution for data hiding

ISSN: 2277 943 Volume 2, Issue 1, October 213 Steganography using LSB bit Substitution for data hiding Himanshu Gupta, Asst.Prof. Ritesh Kumar, Dr.Soni Changlani Department of Electronics and Communication Engineering Lakshmi Narain College of Technology & Science, Bhopal, Madhya Pradesh Abstract Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information. Different applications have different requirements of the steganography technique are used. In the domain of digital images many different image file formats exist, most of them for specific applications. For these different image file formats, different steganographic algorithms exist. But in these paper two methods is discussed image domain and transform domain. The use of LSB algorithm for image domain decreases the MSE value and increase the PSNR value when increase the bit substitution. This work is simulated on MATLAB and results shows the effect of different message bit for hide bit and analysis effect on the results. Keywords- Steganography, LSB, bit-substitution, Image domain, transform domain. 1. INTRODUCTION Steganography is the art of invisible communication by concealing information inside other information. A steganography system consists of three elements: cover-object (which hides the secret message), the secret message and the stego-object (which is the cover object with message embedded inside it.) Given the proliferation of digital images on the internet, and the large redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography [1]. A digital image is described using a 2-D matrix of the color intestines at each grid point (i.e. pixel). Typically, gray images use 8 bits, whereas colored utilizes 24 bits to describe the color model, such as RGB model. The secret bits are written directly to the cover image pixel bytes. Consequently, the spatial domain techniques are simple and easy to implement. The Least Significant Bit (LSB) is one of the main techniques in spatial domain image steganography. On the other hand, frequencybased steganography has higher peak signal-to-noise ratio (PSNR) and is more secure [1]. Unfortunately, frequencybased techniques are more complex and require much more computations. 2. STEGANOGRAPHY In Steganography information data are hiding with a cover image file. The Steganography consist of main four parts Text, Images, Audio/video and Protocol, but in this paper we are only focus on the Image steganography which is subdivided in two part image domain and transform domain as shown in Fig. 1 The Text steganography using digital files is not used very often since text files have a very small amount of redundant data. Given the proliferation of digital images, especially on the Internet, and given the large amount of redundant bits present in the digital representation of an image, images are the most popular cover objects for steganography. To hide information in audio files similar techniques are used as for image files. One different technique unique to audio steganography is masking, which exploits the properties of the human ear to hide information unnoticeably. A faint, but audible, sound becomes inaudible in the presence of another louder audible sound. This property creates a channel in which to hide information. Although nearly equal to images in steganographic potential, the larger size of meaningful audio files makes them less popular to use than images. The term protocol steganography refers to the technique of embedding information within messages and network control protocols used in network transmission [2]. Figure 1: Categories of image steganography To a computer, an image is a collection of numbers that constitute different light intensities in different areas of the image [3]. This numeric representation forms a grid and the individual points are referred to as pixels. The number of bits in a color scheme, called the bit depth, refers to the number of bits used for each pixel [4].. The smallest bit depth in current color schemes is 8, meaning that there are 8 bits used to describe the cooler of each pixel [5]. Monochrome and greyscale images use 8 bits for each pixel and are able to display 256 different colors or shades of grey. Digital color images are typically stored in 24- All Rights Reserved 213 IJARCSEE 676

ISSN: 2277 943 Volume 2, Issue 1, October 213 bit files and use the RGB color model, also known as true cooler [6]. All color variations for the pixels of a 24-bit image are derived from three primary colors: red, green and blue, and each primary cooler are represented by 8 bits [7]. Thus in one given pixel, there can be 256 different quantities of red, green and blue, adding up to more than 16-million combinations, resulting in more than 16-million colors. 3. IMAGE DOMAIN AND TRANSFORM DOMAIN An Image is also known as spatial domain techniques embed messages in the intensity of the pixels directly, while for transform also known as frequency domain, images are first transformed and then the message is embedded in the image. Image domain techniques encompass bit-wise methods that apply bit insertion and noise manipulation. The image formats that are most suitable for image domain steganography are lossless and the techniques are typically dependent on the image format. Steganography in the transform domain involves the manipulation of algorithms and image transforms [8].These methods hide messages in more significant areas of the cover image, making it more robust [9]. Many transform domain methods are independent of the image format and the embedded message may survive conversion between lossy and lossless compression. (1111 11111 1111) When the number 2, which binary representation is 111, is embedded into the least significant bits of this part of the image, the resulting grid is as follows: (1111 1111 11111) (1111 1111 11) (1111 1111 1111) Although the number was embedded into the first 8 bytes of the grid, only the 3 underlined bits needed to be changed according to the embedded message. On average, only half of the bits in an image will need to be modified to hide a secret message using the maximum cover size. Since there are 256 possible intensities of each primary colour, changing the LSB of a pixel results in small changes in the intensity of the colours. These changes cannot be perceived by the human eye - thus the message is successfully hidden. With a well-chosen image, one can even hide the message in the least as well as second to least significant bit and still not see the difference. In the above example, consecutive bytes of the image data from the first byte to the end of the message are used to embed the information. A slightly more secure system is for the sender and receiver to share a secret key that specifies only certain pixels to be changed. Should an adversary suspect that LSB steganography has been used, he has no way of knowing which pixels to target without the secret key. The result stegoimages are shown in Fig.6 Inspecting the images reveal that the distortion is visible for the stego-image for n 4. The metrics for all images are similar. Figure 2: Block diagram of Steganography Fig.2 shows the fundamental block diagram of Steganography. The LSB is the lowest significant bit in the byte value of the image pixel. The LSB based image steganography embeds the secret in the least significant bits of pixel values of the cover image (CVR). 4. LEAST SIGNIFICANT BIT Least significant bit (LSB) insertion is a common, simple approach to embedding information in a cover image [1].The least significant bit (in other words, the 8th bit) of some or all of the bytes inside an image is changed to a bit of the secret message. When using a 24-bit image, a bit of each of the red, green and blue color components can be used, since they are each represented by a byte. In other words, one can store 3 bits in each pixel. An 8 6 pixel image, can thus store a total amount of 1,44, bits or 18, bytes of embedded data. For example a grid for 3 pixels of a 24-bit image can be as follows: (1111 111 11111) (1111 111 11) Figure 3: Test Images Table1: Image matrix parameter on different bit substitution n-bit LSB PSNR (db) MSE 1-bit 17.4173 4751.2 2-bit 22.982 1341.9 3-bit 29.694 324.7878 4-bit 35.2618 78.48 5-bit 41.766 17.4559 6-bit 48.74 3.538 7-bit 57.188.517 8-bit 99 All Rights Reserved 213 IJARCSEE 677

ISSN: 2277 943 Volume 2, Issue 1, October 213 extracting decoded image. Finally compare the histogram response of cover image and on variation of bit substitution ( Fig.9 and Fig.1 ) and also calculate the PSNR and MSE with variation of bit substitution as Table1. 1-bit substitution 2-bit substitution 1-bit substitution 2-bit substitution 3-bit substitution 4-bit substitution 3-bit substitution 4-bit substitution 5-bit substitution 6-bit substitution 5-bit substitution 6-bit substitution 7-bit substitution 8-bit substitution Figure 4: Extracted Images on different bit substitution. 5. SIMULATION RESULTS Two simulations are compute on MATLAB for data hide first the LSB code for hide bit using bit shifting and takes the results, shown in figure4 for 4bit data shifting. Take the test lena and baboon, images for cover image and message image [11] and developed algorithm on MATLAB according to Fig.2. The two simulation are perform first for testing taking monochrome image and second one is color image and gets the result in form of extracted images Fig.4, steganographic images Fig.5, Fig.7, where Fig.8 represent the output of 7-bit substitution 8-bit substitution Figure 5: Steganographic Images on different bit substitution All Rights Reserved 213 IJARCSEE 678

ISSN: 2277 943 Volume 2, Issue 1, October 213 4 Bit Image to Hide Stego image 45 4 35 3 25 2 15 1 5 5 1 15 2 25 Figure 6: 4-bit Image hide by LSB method (Baboon.jpeg) (a) Histogram of Transformed stego image on 1-bit substitution LSB Stego Image 6 5 4 3 2 1 Figure 7: Results from LSB algorithm (Baboon.jpeg) 5 1 15 2 25 (b) Histogram of Transformed stego image on 2-bit substitution 9 8 7 6 5 4 3 2 Figure 8: Textstring Image after LSB Extraction using Acrobat Distiller (Baboon.jpeg) 1 5 1 15 2 25 3 25 2 15 (c) Histogram of Transformed stego image on 3-bit substitution 12 1 8 1 6 5 4 5 1 15 2 25 Figure 9: Histogram of cover image 2 5 1 15 2 25 (d) Histogram of Transformed stego image on 4-bit substitution All Rights Reserved 213 IJARCSEE 679

ISSN: 2277 943 Volume 2, Issue 1, October 213 9 8 7 6 5 4 3 2 1 5 1 15 2 25 (e) Histogram of Transformed stego image on 5-bit substitution 6 5 4 3 2 1 5 1 15 2 25 (f) Histogram of Transformed stego image on 6-bit substitution (g) Histogram of Transformed stego image on 7-bit substitution 3 45 4 35 3 25 2 15 1 5 5 1 15 2 25 6. CONCLUSION In this paper, we analyzed the performance of different cases of LSB steganography. Then proposed the LSB design for bit shifting method and LBS algorithm compare the result there is no any change in original figure and stego figure but whenever textstring is 2-D so extracting image is black and white and color. REFERENCES [1] T. Morkel, J. Eloff and M. Olivier, "An Overview of Image Steganography," The Fifth Annual Information Security South Africa Conference (ISSA25), Sandton, South Africa, July 25. [2] H. Wang, S. Wang, Cyber warfare: Steganography vs. Steganalysis, Communications of the ACM, Vol. 47, No. 1, pp. 76-82, October 24. [3] E. Walia, P. Jain, Navdeep, An Analysis of LSB & DCT based Steganography, Global Journal of Computer Science and Technology, Vol. 1, pp. 4-8., April, 21. [4] Anderson, R.J. & Petitcolas, F.A.P., On the limits of steganography, IEEE Journal of selected Areas in Communications, May 1998. [5] Moerland, T., Steganography and Steganalysis, Leiden Institute of Advanced Computing Science, www.liacs.nl/home/ tmoerl/privtech.pdf [6] Artz, D., Digital Steganography: Hiding Data within Data, IEEE Internet Computing Journal, June 21. [7] Johnson, N.F. & Jajodia, S., Exploring Steganography: Seeing the Unseen, Computer Journal, February 1998. [8] Venkatraman, S., Abraham, A. & Paprzycki, M., Significance of Steganography on Data Security, Proceedings of the International Conference on Information Technology: Coding and Computing, 24. [9] Lee, Y.K. & Chen, L.H., High capacity image steganographic model, Visual Image Signal Processing, 147:3, June 2. [1] Himanshu Gupta, Ritesh Kumar and Soni Changlani, Enhanced Data Hiding Capacity Using LSB-Based Image Steganography Method, International Journal of Emerging Technology and Advanced Engineering, ISSN 225-2459 Volume 3, Issue 6, pp. 212-214, June 213. [11] The image database of the signal [online]. Available: http://sipi.usc.edu/database/ 25 2 15 1 5 5 1 15 2 25 (h) Histogram of Transformed stego image on 8-bit substitution Figure1: Histogram of Transformed stego image on different bit substitution All Rights Reserved 213 IJARCSEE 68