Image encryption algorithm based on the matrix semi-tensor product with a compound secret key produced by a Boolean network

Abstract In this paper, a chaotic image encryption algorithm based on the matrix semi-tensor product (STP) with a compound secret key is designed. First, a new scrambling method is designed. The pixels of the initial plaintext image are randomly divided into four blocks. The pixels in each block are then subjected to different numbers of rounds of Arnold transformation, and the four blocks are combined to generate a scrambled image. Then, a compound secret key is designed. A set of pseudosecret keys is given and filtered through a synchronously updating Boolean network to generate the real secret key. This secret key is used as the initial value of the mixed linear-nonlinear coupled map lattice (MLNCML) system to generate a chaotic sequence. Finally, the STP operation is applied to the chaotic sequences and the scrambled image to generate an encrypted image. Compared with other encryption algorithms, the algorithm proposed in this paper is more secure and effective, and it is also suitable for color image encryption.

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

[2]  Daizhan Cheng,et al.  A Linear Representation of Dynamics of Boolean Networks , 2010, IEEE Transactions on Automatic Control.

[3]  S. Kauffman,et al.  Genetic networks with canalyzing Boolean rules are always stable. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Bowen Li,et al.  Fast-Time Stability of Temporal Boolean Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.

[5]  Tao Xie,et al.  Breaking a novel image fusion encryption algorithm based on DNA sequence operation and hyper-chaotic system , 2014 .

[6]  Yan Gao,et al.  An adjoint network approach to design stabilizable switching signals of switched Boolean networks , 2019, Appl. Math. Comput..

[7]  Guangyong Li,et al.  Quantum image encryption scheme with iterative generalized Arnold transforms and quantum image cycle shift operations , 2017, Quantum Inf. Process..

[8]  D. Cheng,et al.  Analysis and control of Boolean networks: A semi-tensor product approach , 2010, 2009 7th Asian Control Conference.

[9]  Jinde Cao,et al.  The transformation between the Galois NLFSRs and the Fibonacci NLFSRs via semi-tensor product of matrices , 2018, Autom..

[10]  Zhigang Zeng,et al.  Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[11]  Daizhan Cheng,et al.  Block Decoupling of Boolean Control Networks , 2019, IEEE Transactions on Automatic Control.

[12]  Wei Zhang,et al.  A chaos-based symmetric image encryption scheme using a bit-level permutation , 2011, Inf. Sci..

[13]  Hongyu Zhao,et al.  Fast image encryption algorithm based on parallel computing system , 2019, Inf. Sci..

[14]  Jian Wang,et al.  Quantum Image Encryption Algorithm Based on Quantum Key Image , 2019 .

[15]  Kehui Sun,et al.  A fast image encryption algorithm based on compressive sensing and hyperchaotic map , 2019, Optics and Lasers in Engineering.

[16]  Yang Liu,et al.  Observability of Boolean networks via STP and graph methods , 2019, IET Control Theory & Applications.

[17]  Neeru Jindal,et al.  A secure image encryption algorithm based on fractional transforms and scrambling in combination with multimodal biometric keys , 2018, Multimedia Tools and Applications.

[18]  Qiang Zhang,et al.  A novel image fusion encryption algorithm based on DNA sequence operation and hyper-chaotic system , 2013 .

[19]  Fuad E. Alsaadi,et al.  SURVEY ON APPLICATIONS OF SEMI-TENSOR PRODUCT METHOD IN NETWORKED EVOLUTIONARY GAMES , 2020 .

[20]  Guodong Zhao,et al.  A survey on applications of semi-tensor product method in engineering , 2017, Science China Information Sciences.

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

[22]  Jinde Cao,et al.  Stabilization of probabilistic Boolean networks via pinning control strategy , 2020, Inf. Sci..

[23]  Jawad Ahmad,et al.  DNA key based visual chaotic image encryption , 2019, J. Intell. Fuzzy Syst..

[24]  Hao Zhang,et al.  Synchronization of Boolean Networks with Different Update Schemes , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[25]  Lin Teng,et al.  A novel colour image encryption algorithm based on chaos , 2012, Signal Process..

[26]  Ahmed A. Abd El-Latif,et al.  Design and implementation of a simple dynamical 4-D chaotic circuit with applications in image encryption , 2020, Inf. Sci..

[27]  Janier Arias-Garcia,et al.  Image encryption based on the pseudo-orbits from 1D chaotic map. , 2019, Chaos.

[28]  Weiwei Chen,et al.  Bit-level quantum color image encryption scheme with quantum cross-exchange operation and hyper-chaotic system , 2018, Quantum Information Processing.

[29]  Qiong Gong,et al.  Modified diffractive-imaging-based image encryption , 2019, Optics and Lasers in Engineering.

[30]  Feng Xu,et al.  Designing permutation-substitution image encryption networks with Henon map , 2017, Neurocomputing.

[31]  Yiran Chen,et al.  An image encryption algorithm based on chaotic system and compressive sensing , 2018, Signal Process..

[32]  Xingyuan Wang,et al.  A color image encryption algorithm based on Hopfield chaotic neural network , 2019, Optics and Lasers in Engineering.

[33]  Min Meng,et al.  On solutions of the matrix equation AX=B with respect to semi-tensor product , 2016, J. Frankl. Inst..

[34]  Fuad E. Alsaadi,et al.  New developments in control design techniques of logical control networks , 2020, Frontiers of Information Technology & Electronic Engineering.

[35]  Zhihong Zhou,et al.  Image compression–encryption scheme based on hyper-chaotic system and 2D compressive sensing , 2016 .

[36]  Yicong Zhou,et al.  Image encryption using 2D Logistic-adjusted-Sine map , 2016, Inf. Sci..

[37]  Xingyu Yan,et al.  Multi-image encryption scheme based on quantum 3D Arnold transform and scaled Zhongtang chaotic system , 2018, Quantum Information Processing.

[38]  Titus Hilberdink Quasi Kronecker products and a determinant formula , 2018 .

[39]  D. Ravichandran,et al.  DNA Chaos Blend to Secure Medical Privacy , 2017, IEEE Transactions on NanoBioscience.

[40]  Weidong Zhang,et al.  Alternative approach to calculate the structure matrix of Boolean network with semi-tensor product , 2017 .

[41]  Changjiang Bu,et al.  Generalized inverses of tensors via a general product of tensors , 2018 .

[42]  Ahmed A. Abd El-Latif,et al.  An encryption protocol for NEQR images based on one-particle quantum walks on a circle , 2019, Quantum Information Processing.

[43]  Daizhan Cheng Semi-tensor product of matrices——A convenient new tool , 2011 .

[44]  Ming Xu,et al.  A novel image cipher based on 3D bit matrix and latin cubes , 2019, Inf. Sci..

[45]  Hao Zhang,et al.  Synchronization of Asynchronous Switched Boolean Network , 2015, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[46]  Azman Samsudin,et al.  A new hybrid digital chaotic system with applications in image encryption , 2019, Signal Process..

[47]  Jinde Cao,et al.  On the ensemble controllability of Boolean control networks using STP method , 2019, Appl. Math. Comput..

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

[49]  Xingyuan Wang,et al.  Spatiotemporal chaos in mixed linear–nonlinear coupled logistic map lattice , 2014 .

[50]  Xing-yuan Wang,et al.  Analysis and improvement of a chaos-based symmetric image encryption scheme using a bit-level permutation , 2014 .