ISSN:2249-5789 Garima Tomar et al, International Journal of Computer Science & Communication Networks,Vol 2(1), 12-15
Effect of Noise on hidden data Garima Tomar Faculty of Electrical and Electronics,MITS Ujjain
[email protected] Abstract -This paper simulates an effective data hiding technique i.e. steganography based on LSB insertion and RSA encryption in order to provide seven million times better security than the previous work. The Main idea of proposed scheme is to encrypt secret data by RSA 1024 algorithm, convert it in to binary sequence bit and then embedded into each cover pixels by modifying the least significant bits (LSBs) of cover pixels. The result image is also known as steganography image. The PSNR value of this steganography image is 54.34 db. In this paper Baboon image is used for experimental purpous.This steganography image is transmitted through AWGN channel, and performance is simulated. The image and hidden data are reconstructed with the SNR level ≥9 dB. Key words: Steganography, LSB, RSA algorithm, AWGN channel
image, so that it almost becomes impossible for the attacker to discover any embedded message. There are many techniques for encrypting data [5], which vary in their security, robustness, performance and so on. Also, there are many ways for embedding a message into another one. The most popular one is embedding a message into a gray image using LSB [6]. In this method the data is being hidden in the least significant bit of each pixel in the cover image. After hiding data in image the form of image is called stego image. In this paper LSB insertion method is used for embedding data in cover image ,resulting stego image is transmitted through AWGN channel and performance is simulated.
I INTRODUCTION
On internet the amount of digital images has increased rapidly but security of images becomes increasingly important for many applications, like, confidential transmission, military and medical applications. In steganography, the secret message is embedded into an image (or any media) called cover image, and then sent to the receiver who extracts the secret message from the cover image. After embedding the secret message, the cover image is called a stego-image. This image should not be distinguishable from the cover image, so that the attacker cannot discover any embedded message. The security of the transformation of hidden data can be obtained by two ways: encryption and steganography. A combination of the two techniques can be used to increase the data security [1]. In encryption, the message is changed in such a way so that no data can be disclosed if it is received by an attacker [2]. Whereas in steganography [3], the secret message is embedded into an image often called cover image, and then sent to the receiver who extracts the secret message from the cover message [4]. When the secret message is embedded into cover image the it is called a stego-image. The visibility of this image should not be distinguishable from the cover
Fig 1 steganography Mechanism
II DATA HIDING ALGORITHM In the application the user first specifies the data that they would like to hide, which can be in any file format. The application then encrypts this data using the recipient‟s RSA public key. Once the encrypted data is obtained, the procedure described in the following paragraph is repeated for each image in a user‟s image library. Each bit of the encrypted data is compared to the least significant bit of the pixel bytes in an image. The comparisons are made starting from the first byte in the image until the last byte that permits all the data to be hidden in that image. The application cycles through the pixels of the image
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ISSN:2249-5789 Garima Tomar et al, International Journal of Computer Science & Communication Networks,Vol 2(1), 12-15 looking for the block of bytes those results in the least number of LSB changes. A. least significant bit insertion method Least significant bit insertion is a common, simple approach to embed information in a cover file [7]. Usually, three bits from each pixel can be stored to hide an image in the LSBs of each byte of a 24-bit image. The resulting stego-image will be displayed indistinguishable to the cover image in human visual system [18].
adjacent index colours that contrast too much before it inserts the message. This approach works quite well in gray-scale images and may work well in images with related colours [18]. On the other hand, StegCure keeps the advantage of S-Tools and EzStego that is maintaining the image quality, but it can prevent the attack from hackers by restricting user to have only one attempt to perform destego method. If the user has used the wrong destego method for the first time, there is no second attempt to recover the hidden data in the image even though the user has chosen the correct destego method. B Encryption Algorithm
Fig. 2: Least Significant Bit
The last bit of the byte is selected as least significant bit in one bit LSB as illustrated in Figure 2 because of the impact of the bit to the minimum degradation of images [32]. The last bit or also known as right-most bit is selected as least significant bit, due to the convention in positional notation of writing less significant digit further to the right [20]. In bit addition, the least significant bit has the useful property of changing rapidly if the number changes slightly. For example, if 1 (binary 00000001) is added to 3 (binary00000011), the result will be 4 (binary 00000100) and three of the least significant bits will change (011 to 100).
As mentioned previously, the data to be hidden is first encrypted using the RSA public key algorithm. Encrypting the data before hiding it provides defense in depth, and makes the job of the attacker more difficult if their goal is to recover the secret data. The application uses the RSA algorithm for two reasons. First, by using a public key algorithm the need for a private shared key between the sender and recipient of the data is eliminated. Shared keys are impractical because they require a secure way of distributing the key to every person who you may want to communicate with. A public key for a person can be distributed fairly easily by publishing it on a website, or by emailing it to people you expect would need to send you secret information. Second, the RSA algorithm is also widely known and demonstrably secure if large enough prime numbers are used to generate the keys. Using an algorithm such as RSA which is public knowledge is in keeping with the principle of open design of secure software systems. Adhering to this principle was also the reason we chose not to use our own encryption algorithm. III SIMULATED RESULTS
Fig. 3: Example of bit addition
There are numbers of steganograpic tools which employ LSB insertion methods available on the web. For example, S-Tools take a different approach by closely approximating the cover image which may mean radical palette changes. Instead, S-Tools reduce the number of colours while maintaining the image quality, so that the LSB changes do not drastically change colour values. Another tool which is using LSB manipulation is EzStego. It arranges the palette to reduce the occurrence of
Tool used: MATLAB Simulink version 7.0 .The name of image is baboon, size of image is 256x256, and format of image is BMP which we have taken for simulation .Here 256x256 meaning that number of rows and column of pixels, and BMP meaning that the format of image i.e. bit map format. These four images are gray scale images i.e. 8 bits per pixel. The proposed method hides secret data bits in LSB of each pixel so we can hide 65536 secret data bits in an image by using row ×column × n relationship. Where n is no of LSBs used.The results are tabulated in Table 1. In Table 1, the column labeled „Capacity‟ is the number of bits can be embedded into the host-image and the column labeled „PSNR‟ is the peak-signal-to-noise-ratio of
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ISSN:2249-5789 Garima Tomar et al, International Journal of Computer Science & Communication Networks,Vol 2(1), 12-15 the stego-image. The results are the average value of embedding 65536 random bit-streams into the host images. A simulation results when secret data bits are hide in cover image TABLE 1 SIMULATION RESULS WHEN SECRET DATA BITS ARE HIDE IN COVER IMAGE
Name
of
Embedding
the images
secret
PSNR in db
data
capacity in bits Baboon
65536
54.34
Here PSNR is calculated by following relation 1
MSE=𝐻×𝑊
𝐻 𝐼=1.
𝑊 𝐽 =1
Cover image of Baboon
B. simulation results when data stream is transmitted trough awgn for the Baboon picture
𝑃𝑉𝑂𝐹𝐶𝑂𝑉𝐸𝑅 𝐼𝑀𝐴𝐺𝐸 𝐼, 𝐽 −
𝑃𝑉 𝑂𝐹 𝑆𝑇𝐸𝐺𝑂 𝐼𝑀𝐴𝐺𝐸 𝐼, 𝐽 )2 PSNR =1𝑂 log
convolutional coding and viterbi algorithm to detect and correct errors .The experimental results shown in table 2 that how much secret data bits and stego bits are corrected by channel coding. The size of image is 256x256 i.e.65536 total no of pixels or 524288 data streams are transmitted through noisy channel. Additive white Gaussian noises are used in this experiment. The characteristic of this communication system with bit error rate (BER) versus signal noise ratio (SNR, 𝐸𝑏 /𝑁0 , dB) , where 𝐸0 is energy per bit and 𝑁0 is noise spectral density. Such a controlled noise was added in every channel and that stego image is transmitted over the channel bit by bit. The number of error bits was measured at every controlled noise level to obtain BERs for test image during the stego image transmission. The received stego bits are used to reconstruct the stego image, and extract secret data bits by using decryption algorithm.. The error correction results of the proposed method are given in the table 2.
255 2 𝑀𝑆𝐸
(1)
Table 2 simulation results when stego image is transmit through AWGN channel
(2)
SNR IN db
No of bits corrupted through AWGN/524288
No of hidden data bits corrupted through AWGN /65536
0 1 2 3 4 6 8 9 10
41086 29086 11958 6491 3231 1217 86 24 2
5080 3688 1466 815 411 146 14 4 1
Stego image of baboon PSNR =53.94
Fig 4 image used in this simulation
When this image is transmitted through AWGN channel, noises are introduced in it, thereby this stego image may be corrupted by noise and also hidden secret data bits are affected by the noise. The experimental results shown in table 2 that how much stego bits and data bits are corrupted by noise.The solution of this problem is that detects these errors and corrects these errors .In proposd method use channel coding to correct corrupted secret hidden data bits by noise. For this purpouse use
IV CONCLUSION The conclusion of these experimental results is that- The proposed data hiding scheme is an efficient data hiding scheme based on the LSB insertion and RSA encryption method by its PSNR value of image like baboon is 54.00 dB, which is not noticeable by human eyes. Enhance security of hidden data by 7x106 times than the RSA-512 in terms of its time complexity, and 2650 times in space complexity. The steganography image is transmitted through AWGN channel, and performance
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ISSN:2249-5789 Garima Tomar et al, International Journal of Computer Science & Communication Networks,Vol 2(1), 12-15 simulated. The image and hidden data are reconstructed with the SNR level ≥9 dB.
21.
N. F. Johnson, S. Jajodia, “Exploring Steganography: Seeing the Unseen,” IEEEComputer, February 1998, pp.26-34.Image, Vol. 3, pp. 1019-1022. L.Y. Por1, W.K. Lai2, Z. Alireza3, B. Delina4,2008.
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