Abstract— Image encryption process is one of secure communication techniques to get confidentiality and authority of reading data. Encryption techniques should be improved with technological progress to overcome the security problems like the existence of penetration of the network. This paper develop an image encryption technique by encrypt the clusters of image using the generated keys from propose a modified of standard map. In decryption process, a recover image can be obtained by reverse the encryption process and utilize adding instead of clustering. Exploratory results check and demonstrate that the proposed procedure is secure and quick. Keywords— Image encryption, decryption, cluster, standard map. I. INTRODUCTION Image data must be remain protected with the rapid growth of information technology from illegal users over unsecured channels of network. Image security is an application layer to get a safely transfer of the image data. Traditional cryptosystems have a long time to encrypt the image data since the size of image is larger than text size. The main methods to protect a data from unauthorized users are cryptography, steganography, and watermarking. Cryptography is one of the main tools to provide security. It deals with the improvement of techniques for converting data forms between intelligible and unintelligible. There are two main techniques of cryptography: private key cryptography and public key cryptography. In the private key technique, the sender and receiver use a same secret key for encryption and decryption processes. In the public key technique, they use different keys for encryption and decryption processes [1]. The existing algorithms can be divided into three categories: Permutation of position [2,3], transformation of value [4,5], and the combination form [6,7]. An image encryption and compression using prediction error clustering technique is study in [8,9]. This paper focuses on the improvement of private key image encryption algorithm. The proposed algorithm based on preprocessing process that give clusters of image and modify a standard map. The organization of this paper is as follows: proposed image encryption and decryption technique in the first section, Experimental analysis in the second section, and conclusion in the third section. II. PROPOSED IMAGE ENCRYPTION AND DECRYPTION TECHNIQUE Fig. (1) and (2) show a block diagram of encryption and decryption respectively. A technique of image encryption is based on image clustering as preprocessing and random standard map. A standard map in equation (1) is modified into two sub equations to generate a series of keys as a tool for image clusters encryption using a technique in [10]. Standard map can be as follow equations: = + c sin mod 2π …….(1.a) = + mod 2π ………(1.b) A modified Standard map as key generation as in equation (2): = ( + ( − )( = ( + ( − )(
International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2763 Issue 03, Volume 3 (March 2016) www.ijirae.com Image decryption technique uses reverse processes of image encryption and use adding process to recover an image.
Fig 1. Proposed image encryption block diagram
Fig. 2. Proposed image decryption block diagram This paper takes “baboon image” and “peppers image” samples as example. See fig. (3) and (4) respectively.
International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2763 Issue 03, Volume 3 (March 2016) www.ijirae.com
fig. 4. Sample 2 and its histograms In the following sections show the steps of proposed technique: Preprocessing step Input: An original color image with size n x n x 3. Output: Clusters of image each with size qxqx3. 1. Read a color image with size n x n x 3 (e.g. 256x256x3). 2. Split the original image into (m) clusters (e.g. 5 clusters). See fig. (5).
International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2763 Issue 03, Volume 3 (March 2016) www.ijirae.com 3. 4. 5. 6. 7. 8.
Inverse the permutation of B’ using to sort the index (1… Q’). And then XOR the result with round to get a recover 1D array (A’) with size Q’. Compute m’ such that (m’= Q’/ (n*n*3)) is number of clusters as 1D array each with size L’ such that (L’=Q’/ m’). e.g. m’= 1769472/(256*256*3)= 9 and L’= 1769472/9=196608. Use multiple key generations as eq. (3) to generate and each with size L’ and where i=1…m’. And the secret parameters a, b, and k must are similar to a parameters at the sender side (e.g a=10, b=50, k=10). Inverse the permutation of each 1D array of recover cluster using to sort the index (1… L’). Reshape each 1D array of a sorted recover cluster into 2D each with size nxnx3 (e.g. 256x256x3). Adding between these recover 2D of clusters to get a recover image with size nxnx3. IV.
EXPERIMENTAL ANALYSIS
This paper uses 7 analysis measurements between clusters and its permutation, and also between original image and its recover. Tables (1) and (2) show the experimental results of sample 1 and sample 2 respectively.
Fig. 5. Sample 1 clusters and its permutations
Structural Content
Maximum Difference
Normalized Absolute Error
Average Difference
Cluster0 &PCluster0 Cluster1 &PCluster1
6.6607e+03
9.8956
0.2167
1.6202
1.8719
235
1.5203
4.1651e+03
11.9346
0.2743
19.4314
0.6393
181
2.6720
Cluster2 &PCluster2 Cluster3 &PCluster3 Cluster4 &PCluster4 Original & Recover
In the following Table (4) show an encryption and decryption speed results of Sample 1 and Sample2 respectively using processor Intel(R) Core(TM) i7-3537U CPU @ 2.00GHz 2.50 GHz. TABLE 4 ENCRYPTION AND DECRYPTION SPEED RESULTS OF SAMPLE 1 & SAMPLE2
Encryption speed Decryption speed
Sample 1 No. cluster= 5 3.3978 Sec.
Sample 2 No. cluster= 8 3.9046 Sec.
4.2337 Sec.
4.2020 Sec.
V. CONCLUSIONS A proposed system is used to design a technique of image encryption based on image clustering as preprocessing and random standard map. From experimental results show the proposed method has encryption speed and secure. It gives a different size of encrypted image compared with original image size. This cause confuses the attacker who tries getting information about an original image. Decryption process has adding process at last step rather than re-clustering technique. From this point the receiver cannot decrypt image unless he knows the right series of key for each image cluster to recover an original image.
International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2763 Issue 03, Volume 3 (March 2016) www.ijirae.com REFERENCES [1]. N. K. Pareek. “Design and Analysis of A Novel Digital Image Encryption”. International Journal of Network Security & Its Applications (IJNSA), Vol.4, No.2, March 2012. [2].J. W. Yoon and H. Kim, “An image encryption scheme with a pseudorandom permutation based on chaotic maps”, Communication in Nonlinear Science and Numerical Simulation, Vol. 15, No. 12, 2010. pp. 3998-4006. [3].C. K. Nayak, A. K. Acharya and S. Das, “Image encryption using an enhanced block based transformation algorithm”, International Journal of Research and Review in Computer Science, Vol. 2, No. 2, (2011) . pp. 275-279. [4].I. A. Ismail, M. Amin and H. Diab, “A digital image encryption algorithm based a composition of two chaotic logistic map”, International Journal of Network Security, Vol. 11, No. 1, (2010) , pp. 1-10. [5].D. Chen and Y. Chang, “A novel image encryption algorithm based on logistic maps”, Advances in Information Science and Service Sciences, Vol. 3, No. 7, (2011) .pp. 364-372. [6].S. P. Indrakanti and P.S. Avadhani, “Permutation based image encryption technique”, International Journal of Computer Applications, Vol. 28, No. 8, (2011) . pp. 45-47. [7].V. Patidar, N.K. Pareek, G. Purohit and K.K. Sud, “A robust and secure chaotic standard map based pseudorandom permutation-substitution scheme for image encryption”, Optics Communications, Vol. 284, (2011). pp. 4331-4339. [8]. J. Zhou, X. Liu, O. C. Au, and Y. Y. Tang, “Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation”. IEEE transactions on information forensics and security, vol. 9, no. 1, January 2014, pp. 39-50. [9]. H. P. Kaur, R. Kaur, “REVIEW: Improve Image Encryption-Then-Compression System using Prediction Error Clustering with HAAR Wavelet Transform”, International Journal of Research Development & Innovation (IJRDI). Vol. 1, Issue 6, August 2015, pp. 254-257. [10]. S. B. Sadkhan and R. S. Mohammed, “Proposed random unified chaotic map as PRBG for voice encryption in wireless communication”, Procedia Computer Science journal (2015) ELSEVIER pp. 314-323. [11]. A. BenSa¨ıda, “A practical test for noisy chaotic dynamics”, ELSEVIER, 2015.