Hybrid Block Chaotic Compressive Sensing and Chaotic Scrambling Algorithms for Color Image Encryption System
DOI:
https://doi.org/10.31272/jeasd.28.5.11Keywords:
Block Compressive Sensing , Scrambling, Chaotic System, Image EncryptionAbstract
This paper suggests a new image encryption algorithm based on block compressive sensing (BCS) and chaotic scrambling techniques. With compressive sensing (CS), signals can be sampled much lower than the Nyquist-Shannon rate while preserving their information content. BCS can be used as a one-step process by using a 3D logistic chaotic map, the measurement matrix is used as a secret key for encryption. BCS algorithm used an individual image reconstruction algorithm that leverages l_1norm minimization to promote signal sparsity, and a smoothing operator to enhance image quality. An encrypted image is first decomposed into three sub-images based on the tricolor theory; then, a discrete wavelet transform is used to sparsely process the three decomposed images. A 2D Henon map is used to scramble the compressed image after compression. This process further enhances the security of the system by increasing the complexity of the encryption process. The results showed that the proposed system provides better security and has a lower computational complexity than other methods. Furthermore, the proposed system is resistant to known attacks such as brute force and statistical attacks.
References
A. Mohammad A. AL-Hussain and M. K. Mahmood, “Spectrum Sensing of Wide Band Signals Based on Energy Detection with Compressive Sensing,” Journal of Engineering and Sustainable Development, vol. 24, no. 6, pp. 83–90, Feb. 2022, https://doi.org/10.31272/jeasd.24.6.7.
K. M. AlAzawi and J. Q. Kadhim, “Speech Scrambling Employing Lorenz Fractional Order Chaotic System,” DOAJ (DOAJ: Directory of Open Access Journals), vol. 17, no. 4, Oct. 2013.
H. R. Hatem, “Color Image Compression and Encryption Based on Compressive Sensing,” Journal of Engineering and Sustainable Development, vol. 22, no. 1, 2018, Available: https://jeasd.uomustansiriyah.edu.iq/index.php/jeasd/article/view/337/267
P. Refregier and B. Javidi, “Optical Image Encryption Based on Input Plane and Fourier Plane Random Encoding,” Optics Letters, vol. 20, no. 7, pp. 767–769, Apr. 1995, https://doi.org/10.1364/OL.20.000767.
B. Hennelly and J. T. Sheridan, “Optical Image Encryption by Random Shifting in Fractional Fourier Domains,” Optics Letters, vol. 28, no. 4, p. 269, Feb. 2003, https://doi.org/10.1364/ol.28.000269.
N. Singh and A. Sinha, “Gyrator transform-based Optical Image encryption, Using Chaos,” Optics and Lasers in Engineering, vol. 47, no. 5, pp. 539–546, May 2009, https://doi.org/10.1016/j.optlaseng.2008.10.013.
A. Dawood, Q. Thabit, and T. Fahad, “A Comprehensive Review of Color Image Encryption Technology,” Basrah Journal for Engineering Science, vol. 23, no. 1, pp. 56–63, Jul. 2023, https://doi.org/10.33971/bjes.23.1.8.
Q. Thabit, Alaa Al-saffar, and I. Abed, “A New DNA strand-based Encryption Algorithm Using Symmetric Key Generation Table,” Al-Qadisiyah Journal for Engineering Sciences, vol. 15, no. 1, pp. 032–037, Jan. 2022, https://doi.org/10.30772/qjes.v14i4.803.
A. A. Abdul-Kareem and W. Ameen, "Hybrid Image Encryption Algorithm Based on Compressive Sensing, Gray Wolf Optimization, and Chaos," Journal of Electronic Imaging, vol. 32, no. 04, Aug. 2023, https://doi.org/10.1117/1.jei.32.4.043038.
Y. Frauel, A. Castro, T. J. Naughton, and Bahram Javidi, “Resistance of the Double Random Phase Encryption against Various Attacks,” Optics Express, vol. 15, no. 16, pp. 10253–10253, Jan. 2007, https://doi.org/10.1364/oe.15.010253.
E. G. Abdulkadhim, S. H. Dhahi, and M. S. Al-Shemarry, “Review on Various Image Protection Methods,” Journal of Al-Qadisiyah for Computer Science and Mathematics, vol. 15, no. 4, Dec. 2023, https://doi.org/10.29304/jqcsm.2023.15.41364.
A. F. Mohamed, F. Wanis, and Mohamed Mahmoud Ashour, “Enhance Watershed Algorithms Using Principal Component Analysis Capabilities,” Al-Qadisiyah Journal for Engineering Sciences, vol. 17, no. 1, pp. 5–15, Mar. 2024, https://doi.org/10.30772/qjes.2024.145116.1055.
Y. Xiong, J. Gu, and R. Kumar, “Collision in a phase-only Asymmetric Cryptosystem Based on Interference and phase-truncated Fourier Transforms,” Optical and Quantum Electronics, vol. 55, no. 8, Jun. 2023, https://doi.org/10.1007/s11082-023-04943-1.
A. Pedram, V. R. Besaga, F. Setzpfandt, and Ö. E. Müstecaplıoğlu, “Nonlocality Enhanced Precision in Quantum Polarimetry via Entangled Photons,” Advanced Quantum Technologies, Aug. 2024, https://doi.org/10.1002/qute.202400059.
W. Zhang, X. Qiu, D. Zhang, and L. Chen, “Visualizing the Hardy’s Paradox Using Hyper‐Entanglement‐Assisted Ghost Imaging,” Laser & Photonics Review, vol. 17, no. 11, Sep. 2023, https://doi.org/10.1002/lpor.202200865.
X. Huang, Y. Xu, Y. Bai, and X. Fu, “Fast Focusing Method in Ghost Imaging with a Tracking Trajectory,” Optics Letters, vol. 48, no. 21, pp. 5543–5543, Oct. 2023, https://doi.org/10.1364/ol.503027.
A. Sdobnov et al., “Polarization-based Optical Interference Approach For Differential Diagnosis Of Benign And Malignant Tumours” Optics and Lasers in Engineering, vol. 171, pp. 107806–107806, Dec. 2023, https://doi.org/10.1016/j.optlaseng.2023.107806.
M. H. Alhayani, “Real-Time Objects Detection, Tracking, and Counting Using Image Processing Techniques,” Al-Nahrain Journal for Engineering Sciences, vol. 26, no. 1, pp. 24–30, Feb. 2023, https://doi.org/10.29194/njes.26010024.
A. A. Almindelawy and M. H. Ali, “Improvement of Eye Tracking Based on Deep Learning Model for General Purpose Applications,” Al-Nahrain Journal for Engineering Sciences, vol. 25, no. 1, pp. 13–19, Apr. 2022, https://doi.org/10.29194/njes.25010012.
Q. Xu, K. Sun, S. He, and C. Zhu, “An Effective Image Encryption Algorithm Based on Compressive Sensing and 2D-SLIM,” Opt. Lasers Eng., vol. 134, pp. 106178–106178, Nov. 2020, https://doi.org/10.1016/j.optlaseng.2020.106178.
W. Chen, Q. Li, X. Tang, and Q. Pan, “A Digital Watermarking Method for Medical Images Resistant to print-scan Based on QR Code,” Multimedia Tools and Applications, vol. 83, pp. 52197–52218, Nov. 2023, https://doi.org/10.1007/s11042-023-17155-2.
T. Li, Q. Zhao, Y. Wang, H. Zhang, S. Liu, and Y. Su, “Image Sequence Encryption Based on Chaotic Fingerprint Phase Mask and single-shot Digital Holography,” Journal of Optics, vol. 52, no. 3, pp. 1608–1619, Dec. 2022, https://doi.org/10.1007/s12596-022-01064-y.
I. Muniraj et al., “Low Photon Count Based Digital Holography for Quadratic Phase Cryptography,” Optics letters/Optics index, vol. 42, no. 14, pp. 2774–2774, Jul. 2017, https://doi.org/10.1364/ol.42.002774.
A. S. Unde and P. P. Deepthi, “Block Compressive sensing: Individual and Joint Reconstruction of Correlated Images,” Journal of Visual Communication and Image Representation, vol. 44, pp. 187–197, Apr. 2017, https://doi.org/10.1016/j.jvcir.2017.01.028.
Y. Luo et al., “A Robust Image Encryption Algorithm Based on Chua’s Circuit and Compressive Sensing,” Signal Processing, vol. 161, pp. 227–247, Aug. 2019, doi: https://doi.org/10.1016/j.sigpro.2019.03.022.
X. Zhang et al., “Two-level image authentication by two-step phase-shifting interferometry and compressive sensing,” Optics and Lasers in Engineering, vol. 100, pp. 118–123, Jan. 2018, https://doi.org/10.1016/j.optlaseng.2017.08.002.
D. L. Donoho, “Compressed Sensing,” IEEE Transactions on Information Theory, vol. 52, no. 4, pp. 1289–1306, Apr. 2006, https://doi.org/10.1109/tit.2006.871582.
D. Needell and J. A. Tropp, “CoSaMP: Iterative Signal Recovery from Incomplete and Inaccurate Samples,” Applied and Computational Harmonic Analysis, vol. 26, no. 3, pp. 301–321, May 2009, https://doi.org/10.1016/j.acha.2008.07.002.
N. Rawat, B.-H. Kim, Inbarasan Muniraj, G. Situ, and B.-G. Lee, “Compressive Sensing Based Robust Multispectral double-image Encryption,” Appl. Opt., vol. 54, no. 7, pp. 1782–1782, Mar. 2015, https://doi.org/10.1364/ao.54.001782.
T. Chen, M. Zhang, J. Wu, C. Yuen, and Y. Tong, “Image Encryption and Compression Based on Kronecker Compressed Sensing and Elementary Cellular Automata Scrambling,” Optics & Laser Technology, vol. 84, pp. 118–133, Oct. 2016, https://doi.org/10.1016/j.optlastec.2016.05.012.
D. Maluenda, Artur Carnicer, R. Martínez-Herrero, Ignasi Juvells, and Bahram Javidi, “Optical Encryption Using photon-counting Polarimetric Imaging,” Optics Express, vol. 23, no. 2, pp. 655–655, Jan. 2015, https://doi.org/10.1364/oe.23.000655.
W. Chen and X. Chen, “Marked Ghost Imaging,” Applied Physics Letters, vol. 104, no. 25, p. 251109, Jun. 2014, https://doi.org/10.1063/1.4879843.
J. Wu, X. Liao, and B. Yang, “Image Encryption Using 2D Hénon-Sine Map and DNA Approach,” Signal Processing, vol. 153, pp. 11–23, Dec. 2018, https://doi.org/10.1016/j.sigpro.2018.06.008.
Downloads
Key Dates
Received
Revised
Accepted
Published Online First
Published
Issue
Section
License
Copyright (c) 2024 Asaad H. Sahar, Hussein A. Hussein Al-Delfi, Ali Fattah (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.