A Novel Privacy Approach of Digital Aerial Images Based on Mersenne Twister Method with DNA Genetic Encoding and Chaos

Remote Sensing - Tập 12 Số 11 - Trang 1893
Fawad Masood1, Wadii Boulila2,3, Jawad Ahmad4, Arshad Ali5, Syam Sankar6, Saeed Rubaiee7, William J. Buchanan4
1Department of Electrical Engineering, Institute of Space Technology, Islamabad 44000, Pakistan
2College of Computer Science and Engineering, Taibah University, Medina 42353, Saudi Arabia
3RIADI Laboratory, University of Manouba, Manouba 2010, Tunisia
4School of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK
5Institute for Energy and Environment, University of Strathclyde, Glasgow G11 1XQ, UK
6Department of Computer Science and Engineering, NSS College of Engineering, Palakkad 678008, India
7Department of Industrial and Systems Engineering, University of Jeddah, Jeddah, 21589, Saudi Arabia

Tóm tắt

Aerial photography involves capturing images from aircraft and other flying objects, including Unmanned Aerial Vehicles (UAV). Aerial images are used in many fields and can contain sensitive information that requires secure processing. We proposed an innovative new cryptosystem for the processing of aerial images utilizing a chaos-based private key block cipher method so that the images are secure even on untrusted cloud servers. The proposed cryptosystem is based on a hybrid technique combining the Mersenne Twister (MT), Deoxyribonucleic Acid (DNA), and Chaotic Dynamical Rossler System (MT-DNA-Chaos) methods. The combination of MT with the four nucleotides and chaos sequencing creates an enhanced level of security for the proposed algorithm. The system is tested at three separate phases. The combined effects of the three levels improve the overall efficiency of the randomness of data. The proposed method is computationally agile, and offered more security than existing cryptosystems. To assess, this new system is examined against different statistical tests such as adjacent pixels correlation analysis, histogram consistency analyses and its variance, visual strength analysis, information randomness and uncertainty analysis, pixel inconsistency analysis, pixels similitude analyses, average difference, and maximum difference. These tests confirmed its validity for real-time communication purposes.

Từ khóa


Tài liệu tham khảo

Noronha, 2001, Detection and modeling of buildings from multiple aerial images, IEEE Trans. Pattern Anal. Mach. Intell., 23, 501, 10.1109/34.922708

Hu, 2007, Road network extraction and intersection detection from aerial images by tracking road footprints, IEEE Trans. Geosci. Remote Sens., 45, 4144, 10.1109/TGRS.2007.906107

Tang, T., Zhou, S., Deng, Z., Zou, H., and Lei, L. (2017). Vehicle detection in aerial images based on region convolutional neural networks and hard negative example mining. Sensors, 17.

Bashir, I., Ahmed, F., Ahmad, J., Boulila, W., and Alharbi, N. (2019). A Secure and Robust Image Hashing Scheme Using Gaussian Pyramids. Entropy, 21.

Jithin, 2020, Colour image encryption algorithm combining, Arnold map, DNA sequence operation, and a Mandelbrot set, J. Inf. Secur Appl., 50, 102428

Sneha, 2020, A chaotic colour image encryption scheme combining Walsh–Hadamard transform and Arnold–Tent maps, J. Ambient Intell. Humaniz. Comput., 11, 1289, 10.1007/s12652-019-01385-0

Li, S., and Zheng, X. (2002, January 26–29). Cryptanalysis of a chaotic image encryption method. Proceedings of the 2002 IEEE International Symposium on Circuits and Systems, Phoenix-Scottsdale, AZ, USA.

Guo, J.I. (2000, January 28–31). A new chaotic key-based design for image encryption and decryption. Proceedings of the 2000 IEEE International Symposium on Circuits and Systems, Geneva, Switzerland.

Wang, 2015, A novel chaotic image encryption scheme using DNA sequence operations, Opt. Lasers Eng., 73, 53, 10.1016/j.optlaseng.2015.03.022

Alroobaea, R., Rubaiee, S., Bourouis, S., Bouguila, N., and Alsufyani, A. (2019). Bayesian inference framework for bounded generalized Gaussian-based mixture model and its application to biomedical images classification. Inter. J. Imaging Syst. Technol.

Xie, 2017, On the cryptanalysis of Fridrich’s chaotic image encryption scheme, Signal Process., 132, 150, 10.1016/j.sigpro.2016.10.002

Ahmad, 2016, A secure image encryption scheme based on chaotic maps and affine transformation, Multimed. Tools Appl., 75, 13951, 10.1007/s11042-015-2973-y

Ahmad, 2015, Chaos-based diffusion for highly autocorrelated data in encryption algorithms, Nonlinear Dyn., 82, 1839, 10.1007/s11071-015-2281-0

Khan, J.S., ur Rehman, A., Ahmad, J., and Habib, Z. (2015, January 18). A new chaos-based secure image encryption scheme using multiple substitution boxes. Proceedings of the 2015 Conference on Information Assurance and Cyber Security (CIACS), Rawalpindi, Pakistan.

Khan, 2019, A novel chaotic image encryption technique based on multiple discrete dynamical maps, Multimed. Tools Appl., 78, 26203, 10.1007/s11042-019-07818-4

Khan, M., Masood, F., Alghafis, A., Amin, M., and Naqvi, S.I.B. (2019). A novel image encryption technique using hybrid method of discrete dynamical chaotic maps and Brownian motion. PLoS ONE.

Khan, M., Masood, F., and Alghafis, A. (2019). Secure image encryption scheme based on fractals key with Fibonacci series and discrete dynamical system. Neural Comput. Appl., 1–21.

Masood, F., Ahmad, J., Shah, S.A., Jamal, S.S., and Hussain, I. (2020). A Novel Hybrid Secure Image Encryption Based on Julia Set of Fractals and 3D Lorenz Chaotic Map. Entropy, 22.

Ahmad, J., Masood, F., Shah, S.A., Jamal, S.S., and Hussain, I. (2020). A Novel Secure Occupancy Monitoring Scheme Based on Multi-Chaos Mapping. Symmetry, 12.

He, 2001, Chaotic characteristics of a one-dimensional iterative map with infinite collapses, IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 48, 900, 10.1109/81.933333

Soleymani, 2014, A chaotic cryptosystem for images based on Henon and Arnold cat map, Sci. World J., 2014, 536930, 10.1155/2014/536930

Pareek, 2006, Image encryption using chaotic logistic map, Image Vision Comput., 24, 926, 10.1016/j.imavis.2006.02.021

Peng, 2019, Image watermarking algorithm based on quaternion and chaotic Lorenz system, Proc. SPIE, 11179, 111790W

Zhang, 2014, Cryptanalysis of elementary cellular automata based image encryption, Adv. Mater. Res., 981, 372, 10.4028/www.scientific.net/AMR.981.372

Khan, J., Ahmad, J., and Hwang, S.O. (2015, January 27–29). An efficient image encryption scheme based on: Henon map, skew tent map and S-Box. Proceedings of the 6th International Conference on Modeling, Simulation, and Applied Optimization (ICMSAO), Istanbul, Turkey.

Chai, 2017, An image encryption algorithm based on the memristive hyperchaotic system, cellular automata and DNA sequence operations, Signal Process. Image Commun., 52, 6, 10.1016/j.image.2016.12.007

Li, L., Abd-El-Atty, B., El-Latif, A.A.A., and Ghoneim, A. (2017, January 3–6). Quantum color image encryption based on multiple discrete chaotic systems. Proceedings of the 2017 Federated Conference on Computer Science and Information Systems (FedCSIS), Prague, Czech Republic.

Yin, L., Zhao, J., and Duan, Y. (2008, January 18–21). Encryption scheme for remote sensing images based on EZW and chaos. Proceedings of the 9th International Conference for Young Computer Scientists, Hunan, China.

Zhang, 2012, Remote-sensing image encryption in hybrid domains, Opt. Commun., 285, 1736, 10.1016/j.optcom.2011.12.023

Ahmad, 2017, A compression sensing and noise-tolerant image encryption scheme based on chaotic maps and orthogonal matrices, Neural Comput. Appl., 28, 953, 10.1007/s00521-016-2405-6

Huang, 2015, Compression and encryption for remote sensing image using chaotic system, Secur. Commun. Netw., 8, 3659, 10.1002/sec.1289

Ye, 2016, A novel block chaotic encryption scheme for remote sensing image, Multimed. Tools Appl., 75, 11433, 10.1007/s11042-015-2861-5

Zhang, X., and Wang, X. (2018). Remote-sensing image encryption algorithm using the advanced encryption standard. Appl. Sci., 8.

Liu, 2019, A Remote-Sensing Image Encryption Scheme Using DNA Bases Probability and Two-Dimensional Logistic Map, IEEE Access, 7, 65450, 10.1109/ACCESS.2019.2917498

Younas, I., and Khan, M. (2018). A new efficient digital image encryption based on inverse left almost semi group and Lorenz chaotic system. Entropy, 20.

Matsumoto, 1998, Mersenne twister: A 623-dimensionally equidistributed uniform pseudo-random number generator, ACM Trans. Model. Comput. Simul., 8, 3, 10.1145/272991.272995

Matsumoto, M., and Nishimura, T. (2007, August 17). Mersenne Twister: A Random Number Generator (Since 1997/10). Available online: www.math.sci.hiroshima-u.ac.jp/m-mat/MT/emt.

Cokus, S., Matsumoto, M., Nishimura, T., and Eddelbuettel, D. (2020, March 10). RANDMT: Octave Function to Produce Random Numbers via Mersenne Twister. Octave Codes. Available online: https://EconPapers.repec.org/RePEc:cod:octave:c021101.

Jagannatam, A. (2020, March 12). Mersenne Twister—A Pseudo Random Number Generator and Its Variants. Available online: http://cryptography.gmu.edu/~jkaps/download.php?docid=1083.

Watson, 1953, Molecular Structure of Nucleic Acids—A Structure for Deoxyribose Nucleic Acid, Nature, 421, 397

1976, An equation for continuous chaos, Phys. Lett. A, 57, 397, 10.1016/0375-9601(76)90101-8

Xia, G.S., Bai, X., Ding, J., Zhu, Z., Belongie, S., Luo, J., Datcu, M., Pelillo, M., and Zhang, L. (2018, January 18–23). DOTA: A Large-Scale Dataset for Object Detection in Aerial Images. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA.

Khan, F.A., Ahmed, J., Khan, J.S., Ahmad, J., and Khan, M.A. (2017, January 14–17). A novel substitution box for encryption based on Lorenz equations. Proceedings of the 2017 International Conference on Circuits, System and Simulation (ICCSS), London, UK.

Ahmad, J., Larijani, H., Emmanuel, R., and Mannion, M. (2018, January 19–21). Secure occupancy monitoring system for iot using lightweight intertwining logistic map. Proceedings of the 2018 10th Computer Science and Electronic Engineering (CEEC), Colchester, UK.

Rhouma, 2009, OCML-based colour image encryption, Chaos Solitons Fractals, 40, 309, 10.1016/j.chaos.2007.07.083

Liu, 2010, Color image encryption based on one-time keys and robust chaotic maps, Comput. Math. Appl., 59, 3320, 10.1016/j.camwa.2010.03.017

Huang, V.L., Zhao, S.Z., Mallipeddi, R., and Suganthan, P.N. (2009, January 18–21). Multi-objective optimization using self-adaptive differential evolution algorithm. Proceedings of the 2009 IEEE Congress on Evolutionary Computation, Trondheim, Norway.

Liu, 2011, Color image encryption by using Arnold transform and color-blend operation in discrete cosine transform domains, Opt. Commun., 284, 123, 10.1016/j.optcom.2010.09.013

Wu, X., Li, Y., and Kurths, J. (2015). A new color image encryption scheme using CML and a fractional-order chaotic system. PLoS ONE, 10.

Zhang, 2011, A novel image encryption method based on total shuffling scheme, Opt. Commun., 284, 2775, 10.1016/j.optcom.2011.02.039

Ahmed, 2014, A noisy channel tolerant image encryption scheme, Wirel. Pers. Commun., 77, 2771, 10.1007/s11277-014-1667-5

Chebbi, I., Boulila, W., and Farah, I.R. (2015). Big data: Concepts, challenges and applications. Computational Collective Intelligence, Springer International Publishing.

Chebbi, I., Boulila, W., and Farah, I.R. (2016, January 16–19). Improvement of satellite image classification: Approach based on Hadoop/MapReduce. Proceedings of the 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Monastir, Tunisia.

Boulila, 2018, A novel decision support system for the interpretation of remote sensing big data, Earth Sci. Inf., 11, 31, 10.1007/s12145-017-0313-7

Boulila, 2019, A top-down approach for semantic segmentation of big remote sensing images, Earth Sci. Inf., 12, 295, 10.1007/s12145-018-00376-7

Thông tin
Thông tin xuất bản

Remote Sensing

Tập 12 Số 11

1893

Thông tin tác giả