Classical Methods Kirchoff’s golden rule Adaptive Steganography 4LSB substitution technique Model authentication technique
Objective of proposed method Enhance embedding capacity of image . An adaptive number of least significant bitssubstitution method with private stego-key. verify whether the attacker has tried tomodify the secret hidden information in thestego-image. embed the hidden information in the coverimage and use digital signature using a keyto verify the integrity from the stego-image.
Method key1 consists of some gray-level ranges. Each range substitute different fixed number ofbits into LS part of the 8-bit gray value of thepixels. Pixel gray value “g” that fall within the range Ai-Bi is changed by embedding message bits ofsecret information into new gray value “g’ ”. OPAP is used that make the new gray value “g’” fall within the range Ai-Bi. Digital signature of the secret information withthe key2 were obtained and appended with theinformation
Private stego-keygeneration For a gray scale image 8-bit is usedto represent intensity of pixel, so thereare only 256 different gray values anypixel may hold. Different pixels in image may holddifferent gray values let four ranges of gray levels are < A1-B1, A2-B2, A3-B3, A4-B4 > eachrange starting and ending value are in8-bits.
Method to decide Bitsinsertion in each range Let the four gray ranges decided bythe stego-key are <A1-B1, A2-B2, A3-B3, A4-B4> number of pixel count from coverimage in each range are < N1, N2,N3, N4 >. Let the ranges be 0-64, 65-127, 128-191, 192-255 Let ranges hold no of pixels 34,13238, 17116, 35148.
Example :consider a gray level range 0-32, 3 – bitssubstitution are 111 1 : let 00100000 (32) be pixel value of g, 2 : after LSB method, g’ = 001000111 (39) 3 : g’ < 32, K+1 bit of g’ changed from 0 to1 or via- versa (00101111) and checkedagain to fall within range if not K+2 bit ischanged (00111111) and so on until grayvalue fall within range 00011111(31).
IMPLEMENTATION OF ALOS ENCODING ALGORITHM Input: Cover-image, secret message, keys K1, K2. Output: Stego-image. Step1: Read key K1 based on gray-Level ranges. Step2: Read cover image Step3: Decide No. of bits insertion into each range described insection 2.3 Step4: Read the secret message and Convert it into bit stream form. Step5: Read the key K2. Step6: Find the signature using K2 and append with the messagebits. Step7: For each Pixel 7.1: Find gray value g. 7.2: Decide the K-bits insertion based on gray ranges. 7.3: Find K-message bits and insert using method given in section2.4 7.4: Decide and adjust new gray Value g’ using method described inOptimum pixel adjustment process.
EXTRACTION ALORITHM Input: Stego-image, keys K1, K2; Output: Secret information; Step1: Read key K1 based on gray-level ranges. Step2: Read the stego image. Step3: Decide No. of bits extraction into each rangedescribed in section 2.3. Step4: For each pixel, extract the K-bits and save intofile. Step5: Read the key K2 and find the signature of bitstream Step6: Match the signature. Step7: End
Advantages : High hiding capacity compared to LSB Substitutiontechnique. Robust in nature, i.e., highly secure algorithm since twokeys (key-1 and key-2) are used. We get good quality of the stego image. High water marking level. Provides maximum possible payload. Embedded data is imperceptible to the observer.Limitations : High computational complexity. Requires a lot of overhead to hide a relatively bits ofinformation.This can be overcome by using HIGH SPEED
Applications In secret communication system. Military applications. Hiding and protecting of secret data inindustry. Navy and Air force. Business Deals
Results and Discussions Lena and baboon 256 × 256 × 3 colour digital imagesRange Cover imageMax bits that canbe embedded(payload)No of bitsembeddedCapacity(bits/pixel)PSNRRange1Lena 65314951360 3.8016 44.94124768 3.141 55.5705115360 3.2268 40.8688Baboon 60952451360 3.2927 44.76684768 3.2 54.8287115360 3.0352 41.7503Range2Lena 69370051360 3.624 43.4944768 3.7338 53.4812115360 3.6078 40.3313Baboon 70008751360 3.6488 43.24794768 3.7192 53.6941115360 3.5019 40.2084
The input cover image0200400600The histogram of input cover image0 100 200The output stego image0200400600800The histogram of stego image0 100 200Experimental result using Range1 for Baboon cover image
The input cover image0200400600800The histogram of input cover image0 100 200The output stego image05001000The histogram of stego image0 100 200Experimental result using Range2 for Lena cover image
Conclusion Enhanced embedding capacity of image . An adaptive number of least significant bits substitutionmethod with private stego-key. whether the attacker has tried to modify the secrethidden information in the stego-image. embeded the hidden information in the cover image anduse digital signature using a key to verify the integrityfrom the stego-image. Experimental results verify that the proposed model iseffective and efficient.
References S. Dumitrescu, W. X. Wu and N. Memon, “On steganalysis ofrandom LSB embedding in continuous-tone images”,Proceeding of International conference on image Processing,Rochester, NY, pp. 641-644, 2002. A. Cheddad, J. Condell, K. Curran and P. McKevitt,“Enhancing Steganography in digital images”, IEEE - 2008Canadian conference on computer and Robot vision, pp. 326-332,2008. Ko-Chin Chang, Chien-Ping Chang, Ping S. Huang, and Te-ming Tu, “A novel image steganographic method using Tri-way pixel value Differencing”, Journal of multimedia, vol. 3,issue 2, June 2008. K. S. Babu, K. B. Raja, K. Kiran Kumar, T. H. Manjula Devi, K.R. Venugopal, L. M.Pataki, “Authentication of secretinformation in image steganography”, IEEE Region 10Conference, TENCON-2008, pp. 1-6, Nov. 2008. S. K. Moon and R.S. Kawitkar, “Data Security using DataHiding”, IEEE International conference on computationalintelligence and multimedia applications, vol. 4, pp. 247251,Dec 2007