A new set of image encryption algorithms based on discrete orthogonal moments and Chaos theory

In this paper, we introduce a new set of image encryption algorithms based on orthogonal discrete moments and chaos. Two logisitic maps are used to confuse and diffuse the moments’ coefficients obtained using: Tchebichef, Krawtchouk, Hahn, dual Hahn and Racah. An external key of 128 bits is used as the encryption key, some mathematical operations are performed on the key to adapt it as the initial conditions of the logisitic maps. Several experiments are carried out to evaluate the security of the newly introduced algorithms: entropy, key space analysis, statistical and differential attacks. The results obtained show clearly that the proposed algorithms are secure enough to resist any type of known attacks. A comparative study with a similar algorithm operating in the Discrete Transform Domain (DCT) and the state-of-the-art methods validates the superiority of moments’ domains particularly in highly textured images.

[1]  Mandyam D. Srinath,et al.  Orthogonal Moment Features for Use With Parametric and Non-Parametric Classifiers , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Tariq Shah,et al.  An efficient image encryption algorithm based on S8 S-box transformation and NCA map , 2012 .

[3]  Yicong Zhou,et al.  Cosine-transform-based chaotic system for image encryption , 2019, Inf. Sci..

[4]  Saleh Mesbah,et al.  Efficiency and Security of Some Image Encryption Algorithms , 2008 .

[5]  Guangchun Luo,et al.  An image encryption scheme based on chaotic tent map , 2016, Nonlinear Dynamics.

[6]  Sim Heng Ong,et al.  Image Analysis by Tchebichef Moments , 2001, IEEE Trans. Image Process..

[7]  Huazhong Shu,et al.  Image analysis by discrete orthogonal Racah moments , 2007, Signal Process..

[8]  Jan Flusser,et al.  Combined blur and affine moment invariants and their use in pattern recognition , 2003, Pattern Recognit..

[9]  Hassan Qjidaa,et al.  Fractional-order orthogonal Chebyshev Moments and Moment Invariants for image representation and pattern recognition , 2019, Pattern Recognit..

[10]  M. Baptista Cryptography with chaos , 1998 .

[11]  Dimitris E. Koulouriotis,et al.  Image watermarking via separable moments , 2013, Multimedia Tools and Applications.

[12]  David Casasent,et al.  Image segmentation and real-image tests for an optical moment-based feature extractor , 1984 .

[13]  Raveendran Paramesran,et al.  Image analysis by Krawtchouk moments , 2003, IEEE Trans. Image Process..

[14]  John T. Sheridan,et al.  A review of optical image encryption techniques , 2014 .

[15]  S. Agaian,et al.  NPCR and UACI Randomness Tests for Image Encryption , 2011 .

[16]  P. A. Vijaya,et al.  Image Encryption Using Chaotic Maps: A Survey , 2014, 2014 Fifth International Conference on Signal and Image Processing.

[17]  Xiaoling Huang,et al.  Spatial image encryption algorithm based on chaotic map and pixel frequency , 2017, Science China Information Sciences.

[18]  Weisheng Hu,et al.  Chaotic image encryption algorithm using frequency-domain DNA encoding , 2019, IET Image Process..

[19]  Sara Tedmori,et al.  Image cryptographic algorithm based on the Haar wavelet transform , 2014, Inf. Sci..

[20]  Xingyuan Wang,et al.  Image Description With Polar Harmonic Fourier Moments , 2020, IEEE Transactions on Circuits and Systems for Video Technology.

[21]  Vinod Patidar,et al.  Image encryption using chaotic logistic map , 2006, Image Vis. Comput..

[22]  Bharat K. Bhargava,et al.  On the Design of Perceptual MPEG-Video Encryption Algorithms , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[23]  Xingyuan Wang,et al.  Cryptanalysis on a novel image encryption method based on total shuffling scheme , 2011 .

[24]  Abdul Hanan Abdullah,et al.  A weighted discrete imperialist competitive algorithm (WDICA) combined with chaotic map for image encryption , 2013 .

[25]  Yiran Chen,et al.  A novel chaos-based image encryption algorithm using DNA sequence operations , 2017 .

[26]  Rachid Benouini,et al.  Image analysis using new set of separable two-dimensional discrete orthogonal moments based on Racah polynomials , 2017, EURASIP J. Image Video Process..

[27]  J. Fridrich Symmetric Ciphers Based on Two-Dimensional Chaotic Maps , 1998 .

[28]  Pingping Zeng,et al.  Image encryption based on a reality-preserving fractional discrete cosine transform and a chaos-based generating sequence , 2013 .

[29]  H.M. Elkamchouchi,et al.  Measuring encryption quality for bitmap images encrypted with rijndael and KAMKAR block ciphers , 2005, Proceedings of the Twenty-Second National Radio Science Conference, 2005. NRSC 2005..

[30]  Muhammad Khurram Khan,et al.  Dynamic weighted discrimination power analysis: A novel approach for face and palmprint recognition in DCT domain , 2010 .

[31]  Je Sen Teh,et al.  Implementation and practical problems of chaos-based cryptography revisited , 2020, J. Inf. Secur. Appl..

[32]  R. Mukundan,et al.  A Fast 4 $\times$ 4 Forward Discrete Tchebichef Transform Algorithm , 2007, IEEE Signal Processing Letters.

[33]  Shiguo Lian,et al.  Multimedia Content Encryption: Techniques and Applications , 2008 .

[34]  Rong-Jian Chen,et al.  Image Encryption and Decryption Using SCAN Methodology , 2006, 2006 Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06).

[35]  Naveen K. Chilamkurti,et al.  An encryption algorithm based on combined chaos in body area networks , 2017, Comput. Electr. Eng..

[36]  Osama S. Farag Allah,et al.  Encryption Efficiency Analysis and Security Evaluation of RC6 Block Cipher for Digital Images , 2007 .

[37]  Chen Juan,et al.  An image encryption algorithm based on spatiotemporal chaos in DCT domain , 2010, 2010 2nd IEEE International Conference on Information Management and Engineering.

[38]  Nikolaos G. Bourbakis,et al.  A General Cryptanalysis of Permutation-Only Multimedia Encryption Algorithms , 2004 .

[39]  Seong Oun Hwang,et al.  An Experimental Comparison of Chaotic and Non-chaotic Image Encryption Schemes , 2015, Wirel. Pers. Commun..

[40]  Dimitris E. Koulouriotis,et al.  Efficient and accurate computation of geometric moments on gray-scale images , 2008, Pattern Recognit..

[41]  Robert A. J. Matthews,et al.  On the Derivation of a "Chaotic" Encryption Algorithm , 1989, Cryptologia.

[42]  Claude E. Shannon,et al.  Communication theory of secrecy systems , 1949, Bell Syst. Tech. J..

[43]  Wen-Hsiang Tsai,et al.  Moment-preserving edge detection and its application to image data compression , 1993 .

[44]  Osama S. Faragallah,et al.  Encryption Efficiency Analysis and Security Evaluation of RC6 Block Cipher for Digital Images , 2007, 2007 International Conference on Electrical Engineering.

[45]  Wei Wang,et al.  A novel digital image encryption algorithm based on wavelet transform and multi-chaos , 2016 .

[46]  AhmadJawad,et al.  An Experimental Comparison of Chaotic and Non-chaotic Image Encryption Schemes , 2015 .

[47]  Rui J. P. de Figueiredo,et al.  Robot sensing techniques based on high-dimensional moment invariants and tensors , 1992, IEEE Trans. Robotics Autom..

[48]  Jiye Liang,et al.  The Information Entropy, Rough Entropy And Knowledge Granulation In Rough Set Theory , 2004, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[49]  Alexandros André Chaaraoui,et al.  Visual privacy protection methods: A survey , 2015, Expert Syst. Appl..

[50]  Alireza Khotanzad,et al.  Recognition and pose estimation of unoccluded three-dimensional objects from a two-dimensional perspective view by banks of neural networks , 1996, IEEE Trans. Neural Networks.

[51]  Jing Xu,et al.  Dynamic weighted discrimination power analysis in DCT domain for face and palmprint recognition , 2010, 2010 International Conference on Information and Communication Technology Convergence (ICTC).

[52]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[53]  Zbigniew Kotulski,et al.  Discrete chaotic cryptography , 1997 .

[54]  Hassan Qjidaa,et al.  Efficient 3D object classification by using direct Krawtchouk moment invariants , 2018, Multimedia Tools and Applications.

[55]  Robert B. McGhee,et al.  Aircraft Identification by Moment Invariants , 1977, IEEE Transactions on Computers.

[56]  Fathi E. Abd El-Samie,et al.  Wavelet fusion for encrypting images with a few details , 2016, Comput. Electr. Eng..

[57]  Olaf Kübler,et al.  Complete Sets of Complex Zernike Moment Invariants and the Role of the Pseudoinvariants , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[58]  Xingyuan Wang,et al.  A novel chaotic block image encryption algorithm based on dynamic random growth technique , 2015 .

[59]  ChaaraouiAlexandros Andre,et al.  Visual privacy protection methods , 2015 .

[60]  Rachid Benouini,et al.  3D image analysis by separable discrete orthogonal moments based on Krawtchouk and Tchebichef polynomials , 2017, Pattern Recognit..

[61]  Xuemin Zhang,et al.  Color image chaos encryption algorithm combining CRC and nine palace map , 2019, Multimedia Tools and Applications.

[62]  Kar-Seng Loke,et al.  Image reconstruction using various discrete orthogonal polynomials in comparison with DCT , 2007, Appl. Math. Comput..

[63]  Xin-Wen Wu,et al.  On the Security of Permutation-Only Image Encryption Schemes , 2016, IEEE Transactions on Information Forensics and Security.

[64]  Xuelong Li,et al.  A local Tchebichef moments-based robust image watermarking , 2009, Signal Process..

[65]  Osama M. Abu Zaid,et al.  Quality of Encryption Measurement of Bitmap Images with RC6, MRC6, and Rijndael Block Cipher Algorithms , 2007, Int. J. Netw. Secur..

[66]  Jan Sher Khan,et al.  Chaos based efficient selective image encryption , 2018, Multidimensional Systems and Signal Processing.

[67]  Minghui Du,et al.  A symmetrical image encryption scheme in wavelet and time domain , 2015, Commun. Nonlinear Sci. Numer. Simul..

[68]  Qixiang Mei,et al.  An efficient pixel-level chaotic image encryption algorithm , 2018, Nonlinear Dynamics.

[69]  Huazhong Shu,et al.  Image Analysis by Discrete Orthogonal Hahn Moments , 2005, ICIAR.

[70]  Alireza Khotanzad,et al.  Invariant Image Recognition by Zernike Moments , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[71]  M. Teague Image analysis via the general theory of moments , 1980 .

[72]  Qing Liu,et al.  An Improved Image Encryption Method Based on Total Shuffling Scheme , 2011 .

[73]  Lu Xu,et al.  A novel chaotic image encryption algorithm using block scrambling and dynamic index based diffusion , 2017 .

[74]  Nanning Zheng,et al.  ADVANCES IN MACHINE VISION, IMAGE PROCESSING, AND PATTERN ANALYSIS , 2006 .

[75]  Sugata Ghosal,et al.  Orthogonal moment operators for subpixel edge detection , 1993, Pattern Recognit..

[76]  Huazhong Shu,et al.  Image analysis by discrete orthogonal dual Hahn moments , 2007, Pattern Recognit. Lett..

[77]  Jan Flusser,et al.  Pattern recognition by affine moment invariants , 1993, Pattern Recognit..

[78]  Salwa K. Abd-El-Hafiz,et al.  Symmetric encryption algorithms using chaotic and non-chaotic generators: A review , 2015, Journal of advanced research.

[79]  Dimitris E. Koulouriotis,et al.  Computation strategies of orthogonal image moments: A comparative study , 2010, Appl. Math. Comput..