Effective and Key Sensitive Security Algorithm For An Image Processing Using Robust Rubik Encryption & Decryption Process
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1 Effective and Key Sensitive Security Algorithm For An Image Processing Using Robust Rubik Encryption & Decryption Process Seetaiah Kilaru, Yojana Kanukuntla, Asma Firdouse, Mohammad Bushra & Sindhu chava Research Scholor, University of Birmingham kilaru4sbit@gmail.com, yojanak5@gmail.com, asma.firdouse03@gmail.com, bushra496.ece@gmail.com Abstract - Encryption and Decryption are the essential processes in multimedia processing. Especially, in digital image processing, the importance of these two is high. Digital image processing facing several problems in recent times, those are protection of owner rights and designing of perfect encryption algorithm against hacker attacks. In recent years, different algorithms proposed based on the chaotic systems. But this proposed algorithm offers low space and limited security. Hence, this paper aims to propose novel algorithm based on the toy principle Rubik cube. Here, XOR operator along with two secret s is used to design algorithm. The results also showed that the proposed algorithm is effective in cases of eye sensitivity and sensitivity. Keywords : Encryption, decryption, Rubik cube and secret. I. ITRODUCTIO In recent years, the growth of technology reached its zenith stage. It is possible to convert any form of data into desired domain. For example the image information may be stored by using numerical or any other standard format. This process also adversely effects on the several issues like copyright protection and protection of ownership rights. As technology increasing its level, it was also noticed that illegal copying also increased. Hence, it is recommendable to define efficient and robust encryption methods. This paper concentrates on the process of designing an algorithm for image processing based on the toy Robik Cube. Encryption is the method to convert the original form of data into unreadable format. Digital watermarking is the method to embed ownership rights into the multimedia images. The combination of these two techniques may increase the data protection. Till now, there are several encryption methods are available such as Rivest Shamir Adleman (RSA), International Data Encryption Algorithm (IDEA) and etc... But no one is preferable for the fast and real time communication in Image encryption. Image encryption broadly classified into three types. They are 1. Pixel Transformation 2. Value Transformation 3. Chaotic Transformation Value Transformation: Based on Intensity Hue Saturation (IHS), the transformation of pixel can be done. The total image is divided into different color spaces and each color space is encrypted by using the different approach. Pixel Transformation: The transformation is possible by using different mechanisms such as Peano-Hilbert curves and permutation-diffusion architecture. These types of processes may use the pixel transformation or pixel shuffling, depends on the criteria. Chaotic Transformation: The origin for this one is pixel transformation only. It is novel pixel shifting method which generates chaotic sequences and is used as a encryption sequences. It used 3D cat map to shuffle pixels within image. This paper presents a novel method for image encryption by using Rubik Cube principle. In this proposed principle, the two secret codes are used. These secret codes perform XOR operation with odd rows and columns and Bitwise XOR with even rows and columns in an image. umerical simulation was done to test the efficiency and validity. The following algorithm shows detailed analysis of proposed algorithm. II. RUBIK S CUBE ECRYPTIO Let size of an image is M (M rows and columns). 86
2 I 0 was the grey scale image with the number of bits = α 1. Generate the vector S R for M and S C for. elements in these two vectors will use the set of variables like {0, 1, 2.2 α -1}. It is important to maintain the values of these S values are constant. 2. ow, define counter to do iteration process. Initialize the counter iterations to zero before process i.e. ITER = Do the iteration process until it reaches the maximum chances, i.e. ITER MAX 4. After several iterations, try to increment the counter i.e. ITER+1 5. As there are α bits are there in an image, calculate the sum of all elements in a defined row as α(i) i = j =1 I(i, j) i= 1,2,3,..M 6. For Row based operation From the value of α(i), calculate Modulo 2 and denote it as M α(i), if this value is 0, it follows the right circular shift. If it is 1, then it follows the left circular shift. 7. For column based operation the sum of all elements in a defined row as α(i) β j = j =1 I(i, j) j= From the value of β(j), calculate Modulo 2 and denote it as M α(j), if this value is 0, it follows the up circular shift. If it is 1, then it follows the down circular shift. 9. Repeat the steps 5-8 several times, which creates the Scrambled message, denoted as I SCR 10. Using S C, calculate bitwise XOR for each row and using S R, calculate bitwise XOR for each column. For row operations III. indicates the end of encryption process and if not, all process repeats from step 3. RUBIK S CUBE DECRYPTIO It The input to decrypt the image will obtain from I EC. 1. Initialize ITER as zero which represents the system is in relaxed mode. 2. Increment the counter for first shift which represents the starting status. ITER = ITER+1 3. For vector S R, apply bitwise XOR operation for each column of I EC and for vector S C, apply bitwise XOR operation for each column. 4. For row operations For column operation 5. Column based operation Calculate sum of all components which are in that column J and denote it as β SCR(j). j=1,2,3. 6. From the value of βscr(j), calculate Modulo 2 and denote it as M βscr(j), if this value is 0, it follows the up circular shift. If it is 1, then it follows the down circular shift 7. Row based operation Calculate sum of all components which are in that column J and denote it as β SCR(j). αscr(i) = j =1 ISCR(i, j) j=1,2,3.m For column operation 11. When the condition reaches ITER which is approximately equal to ITER MAX, then it 8. From the value of αscr(i), calculate Modulo 2 and denote it as M αscr(i), if this value is 0, it follows the right circular shift. If it is 1, then it follows the left circular shift 9. When the condition reaches ITER which is approximately equal to ITER MAX, then it 87
3 indicates the end of encryption process and if not, all process repeats from step 2. IV. EXPERIMETAL RESULTS 2. Unified Average Changing Intensity (UACI) and it can be given as Human Eye Sensitivity test: Fig: lena (original) Fig: Baboon (original) The following table shows the measurements of PCR and UACI. Table1: PCR VS UACI Image PCR UACI Lena Baboon Checkerboard Key sensibility test: The proposed algorithm is very high sensitive in nature and small difference in should produce huge changes in the output. The following figures show the examples of different values. (For encryption). Fig: check (original) Fig: lena for 1 Fig: lena for 2 Fig1: original and encrypted results The above figures show the original and encrypted images. All images are in the size of But, there is no similarity between related images. In human perception view, the similarity index is almost zero. To mention numerically the difference between original and encrypted measures, there are two different measures are there. They are 1. umber of Pixel Change Rate (PCR) and it can be given as Fig: baboon for 1 Fig: baboon for 2 Fig: checker for 1 Fig: checker for 2 Fig 2: performance with 1 and 2 The following figures show the examples of different values. (For decryption) 88
4 Fig 3: decryption with right and wrong s From the results, it is clear that the decryption change leads to change in result. It represents not a normal change, but with the huge difference. Decryption is possible only for the designer who designed the encryption process. Even the third party try to modify it, it will take a huge time for him/her to understand exactly what was the correct order of information. The small Rubik cube toy setting is quite difficult for us because of its complex phenomenon in nature. The image has million number of pixels and it is too difficult for the third party to rearrange into original order. V. COCLUSIO The main motto behind this algorithm is to create confusion between the original and encrypted images in most possible manner. XOR operator is applied to rows and columns of an image in such a way that using the same. After that is flipped and applied again to the same number of rows and columns to reconstruct the image. Experiment results showed that the proposed algorithm is so sensitive against the different s. Perfect encryption and decryption technique only leads to the perfect output generation. Hence, this method is so secure and sensitive; both are essential qualities for an efficient algorithm. VI. REFERECES [1] C. K. Huang, H. H. ien, S. K. Changchien, and H. W. Shieh, Image encryption with chaotic random codes by grey relational grade and Taguchi method, Optics Communications, vol. 280, no. 2, pp , [2] S. Mazloom and A. M. Eftekhari-Moghadam, Color image encryption based on Coupledonlinear ChaoticMap, Chaos, Solitons and Fractals, vol. 42, no. 3, pp , [3] Y. Tang, Z. Wang, and J. A. Fang, Image encryption using chaotic coupled map lattices with time-varying delays, Communications in onlinear Science and umerical Simulation, vol. 15, no. 9, pp , [4] C. E. Shannon, Communication theory of secrecy systems, Bell System Technical Journal, vol. 28, no. 4, pp , [5] O. Edward, Chaos in Dynamical Systems, Cambridge University Press, Cambridge, UK, 2nd edition, [6] Q. Guo, Z. Liu, and S. Liu, Color image encryption by using Arnold and discrete fractional random transforms in HIS space, Optics and Lasers in Engineering, vol. 48, no. 12, pp , [7] Z. Liu, H. Chen, T. Liu et al., Image encryption by using gyrator transform and Arnold transform, Journal of Electronic Imaging, vol. 2, no. 4, pp , [8] T. Xiang, X. Liao, G. Tang, Y. Chen, and K.W.Wong, A novel block cryptosystem based on iterating a chaotic map, Physics Letters, Section A, vol. 349, no. 1 4, pp , [9] Z. Lin and H. Wang, Efficient image encryption using a chaos-based PWL memristor, IETE 89
5 Technical Review, vol. 27, no. 4, pp , [10] Fengxi, S., G. Zhongwei and M. Dayong, Feature Selection Using Principal Component Analysis. ICSEM, 1: [11] Kai-zhi, Y., C. Ying-lei and J. Liu, A method for extracting the text feature of SAR image based on co-occurrence matrix th International Congress on Image and Signal Processing (CISP), Telecommun. Eng. Inst., Air Force Eng. Univ., Xi'an, China, 4: [12] Lifang, W., L. Xingsheng, Y. Songlong and X. Peng, A novel generation cryptosystem based on face features IEEE 10th International Conference on Signal Processing, Oct. 2010, Sch. of Electron. Inf. Control Eng., Beijing Univ. Technol., Beijing, China, pp:
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