HSI Color Space Conversion Steganography using Elliptic Curve

Transcription

1 HSI Color Space Conversion Steganography using Elliptic Curve Gagandeep Kaur #1, Er.Gaurav Deep *2 # Department of computer Engineering, Punjabi University, Patiala Patiala, Punjab, India * Assistant professor, Department of Computer Engineering, Punjabi University, Patiala Patiala, Punjab, India Abstract- Information is very essential part of every organization, But when we transfer data on network it becomes very important that data should not go to the wrong(unauthorized) person hands. Today network security plays a very important role to maintain a Security in every organization. There are number of techniques are available in the market Cryptography and steganography techniques are one of them with the help of these techniques we can secure our data. Now a day s with the combination of both technique becomes very popular.in this paper we have introduced a new techniques in which different conversions are applied that will improve the security level of hidden image.we have used Secret key for encryption. It means that only authorized person can access the hidden data and use of secret key with Transform domain method we can hide the data in different locations of images. As a result it is difficult to extract the exact position of hidden information with retrieval method. Using our proposed method PSNR gives better result because we have applied different conversions and changes very small number of bits using Transform method. Keywords : Hidden image,cover image, Conversions, Steganography, stego image,transform method for data hiding. I INTRODUCTION Steganography is an art of hiding data inside data. Most of the times this technique is used to hide the secret data inside the cover image It does not means to alter the structure of the secret message. Network security is an essential requirement of digital media. To make it secure over a digital medium various techniques/methods have been proposed. Using these two techniques we have provide a step further technique to encrypt the message The encrypted message could be seen by anyone but cryptography make the messge not understandable.on the other hand Steganography is hiding the message in another medium so that nobody will notice the message. Features of good Steganography: 1.Capacity 2.Robustness 3. Undetectabilty 4. Noise of signal 5. Invisibility II LITRATURE REVIEW There are lots of techniques available that implement steganography on a variety of different electronic medium but images are main source to hiding data. M. Masud Karim, Md. Saifur Rahman, Md. Ismail Hossain[1] In this paper author introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. Using this approach substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information. Chi Zhang and P.Wang[2] have proposed a method that is based on K-means algorithm in HSI space and has the advantages over those based on RGB space. Hue, and intensity components are fully utilized.this paper gives the defination of the distance and the center in the hue space, based on which the hue-clustering, algorithm is Implemented. 63

2 Piyush Marwaha1, Paresh Marwaha[3] In this paper author propose an advanced system of encrypting data that combines the features of cryptography, steganography along with multimedia data hiding. This system will be more secure than any other these techniques alone and also as compared to steganography and cryptography combined systems. Nadeem Akhtar, Pragati Johri, Shahbaaz Khan[4] In this paper work is concerned with implementing Steganography for images, with an improvement in both security and image quality.. In this technique, certain least significant bits of cover image are inverted after LSB steganography that co-occur with some pattern of other bits and that reduces the number of modified LSBs. III STEGANOGRAPHY TECHNIQUES 1. Text Strganography 2. Image Steganography 3. Audio Steganography 4. Video Steganography IV IMAGE STEGANOGRAPHY Images are the main source for hiding secret data.an image is a collection of numbers of different light intensities. Different types of images are used in image steganography.in images there are different type of file formats are exit. Each of file format has its own specific advantages.different steganographic algorithms exist, for these different type of image file formats. The basic formula that provide the genric description of steganographic process:- Cover image + hidden information =Stego image Cover image is the main source in which we can hide the hidden object, it can be anything like text, images, audio, video etc. The size of cover image always be larger than the hidden object. The resultant image is known as stego image. With the help of PSNR we can mesure the quality of stego image. PSNR is most easily defined via the mean squared error (MSE) The PSNR is defined as: PSNR= 10 LOG 10 ( R 2 ) MSE Larger dicates better quality of the image or in other terms lower distortion. The larger the PSNR value the smaller the possibility of visual attack by human eye. Fig 1. Types of Image Steganography Image steganography can be further divided into two techniques in which we can hide data according to our requirement. These two are:- Spatial domain Transform method Spatial domain:- The simplest approach to hiding data inside an image is called LSB (Least Significant bit ). Using this method least significant bit of cover image is convert with the hidden data This is very popular and simple method to hiding data. Transform method:- Transform technique has advantage over the spatial domain method.the number of complex algorithms have been suggested Using this technique data will never be lost during compression, cropping and image processing. V COLOUR MODELS There are different types of color models are avalible. Each model has its own advantages. In this paper we will study only two color model RGB and HSI because these two model will use further in our methodology. 64

3 RGB COLOR MODEL:- It stands for Red,Green and Blue it is the oldest model among number of colours models.rgb is additive color model because when we combine red, green and blue light we will get white light. Each RGB color model contain 8 bit for Red 8 bits for Green and 8 bits for Blue color. Digital images are typically stored in either 24-bit (RGB) or 8- bit (Greyscale) files. The main purpose of the RGB colour model is for the sensing, representation, and display of images in electronic systems, such as televisions and computers, though it has also been used in conventional. HSI COLOR MODEL:- This model is a combination of three terms Hue, Saturation and intensity. This model is very important and attractive color model for image processing applications because it represents colors similarly how the human eye senses colors. Using this model there are three layers Hue, saturation and intensity. In each and every layer we can embed data. Extraction of embed data will be very tough using this model.this model is mainly use for to hide large amount of data. The definition of layers are - Hue: it means a pure color and combination of two primary colors, where one of the two primary colors has full intensity. Saturation: It gives a measure of the degree to which a pure color is diluted by white light. Intensity: It is denoted as the distance up the axis from black. 0 degrees is RED,120 degrees is GREEN,240 degrees is BLUE. the hidden data user will save the stego image at any location The following formula, we will use in our proposed methods:- Secret image + Encryption on Secret image + RGB to HSI conversion = Stego image Fig 2: Flow chart of our proposed method On a receiver side we will load the stego image that we have to store at particular location then extract the hidden object from Stego image. On the next step again we will perform reverse conversion HSI to RGB to decrypt the image. VII. EXPERIMENTAL RESULT AND DISCUSSION Experimental results are given in this section define the the performance of our proposed method. We have used RGB (true color) image as the cover image. Small size image is used as the hidden information. VI. PROPOSED METHOD In our purposed method, first sender will take secret image with lower resolution and perform encryption on that hidden image using Elliptic curve method with secret key. In the next step encrypted hidden image will be convert into RGB color model to HSI color model for create illusion to the unauthorized person. The size of cover image should be larger than the hidden object. After embedded 65 Fig. 3 Original cover image The hidden information used in our proposed method is shown Below:

4 IMAGES PSNR CITY Fig.4 Hidden information The procedure to get stego image from cover image by using our proposed method is shown below: = Stego image Secret image +encrypted +conversion + Cover image Image RGB to HSI Fig 5 Stego image produced by using hidden infornation We have used RGB (true color) images named Lena as hidden image. This image is shown in Fig. 9. The cover information which is used to hide information is shown in Fig. 8.In the first step we will encrypt the hidden information with secret key then perform conversion RGB to HSI on encrypted image, with the help of transform method we have embedded data into cover image. In fig 10 define the procedure that how we get stego image from cover image. These stego image we can save at any location. Fig 6 cover image before embedded data Fig 7 cover image after embedded data Table I The experimental results for the proposed method VIII. COMPARISON The experimental results by applying our proposed method on standard images is compared with other methods we have Secret key with RGB color model and Four Neighbour, Eight Neighbour and Diagonal Neighbour methods modify 3 or more bits of a pixel. But for the same capacity our proposed scheme modifies with transform method. Cover Images four Neighbour method RGB with Secret key our method CITY LENA Table II Comparison results with RGB model with Secret key method and four neighbour methods IX.CONCLUSION The experimental results show that the proposed method is an Effective way to integrate hidden information reporting without distortion. And with the use of conversion it becomes very difficult for the unauthorized users to identify the changes in stego image and it gives a way to secure the information from illegal user. Our proposed method provides better PSNR value where larger dicates better quality of the image or in other terms lower distortion. 66

5 X. REFERENCES [1] Alaa A. Jabbar Altaay, Shahrin bin Sahib, Mazdak Zamani, An Introduction to Image Steganography Techniques, IEEE 2013 [2] S. M. Masud Karim, Md. Saifur Rahman, Md. Ismail Hossain, A New Approach for LSB Based Image Steganography using Secret Key IEEE 2011 [3] Sumeet Kaur, Savina Bansal, R. K. Bansal, Steganography and Classification of Image Steganography Techniques IEEE 2014 [4] Nadeem Akhtar, Shahbaaz Khan, Pragati Johri, An Improved Inverted LSB Image Steganography IEEE2014. [5] Chamkor singh, Gaurav Deep, Cluster Based Image Steganography Using Pattern Matching, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) Volume 2, Issue 4, July August 2013 [6] C. Kessler. (2001). Steganography: Hiding Data within Data. An edited version of this paper with the title "Hiding Data in Data".Windows & NETMagazine. y/ steganography.html [7] Chi Zhang and P.Wang A new method of colour image Segmentation based on intensity and Hue Clustring IEEE