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Kaotik Haritalarla Gerçekleştirilen Alt-Görüntü Karıştırma, Bit-Seviyesi Permütasyon ve Difüzyon ile Bir Görüntü Şifreleme Yöntemi

Year 2022, Volume: 9 Issue: 2, 708 - 720, 31.05.2022
https://doi.org/10.31202/ecjse.995766

Abstract

Görüntülerin bir kanal üzerinden güvenli bir şekilde iletilmesi kriptoloji teknikleri ile sağlanabilir. Kaotik haritalar yardımıyla bir görüntünün şifrelenmesi, güvenliği ve kimlik doğrulamasını mümkün kılar. Bu makale, üç ana adımdan oluşan bir görüntü şifreleme yöntemi sunmaktadır: Alt görüntü karıştırma, bit seviyesinde permütasyon ve difüzyon. Alt görüntü karıştırma adımı, önerilen yöntemin sağlamlığını artırmak için bir lojistik harita kullanılarak gerçekleştirilmiştir. Bit seviyesi permütasyon işleminde, her pikselin en yüksek dört biti elde edilir. Bit düzeyinde satır ve sütun dönüşümleri, kaotik bir çadır haritası tarafından oluşturulan diziler kullanılarak uygulanmıştır. Son olarak, difüzyon adımında görüntünün piksellerinin değerleri değiştirilmiştir. Lojistik harita ve çadır haritasından elde edilen iki farklı kaotik dizi kullanılmıştır. Şifreleme için gizli anahtar olarak beş farklı parametre seçilmiştir. Önerilen yöntemin performansı çeşitli analiz yöntemleri ile test edilmiştir. Anahtar uzay analizi, önerilen yöntemin kaba kuvvet saldırılarına dayanabileceğini göstermektedir. Ayrıca yöntemin gizli anahtarlara karşı oldukça hassas olduğu da kanıtlanmıştır. Histogram analizi, şifrelenmiş görüntünün piksellerinin eşit olarak dağıldığını göstermektedir. Ayrıca şifrelenmiş görüntüde komşu pikseller arasındaki korelasyon düz görüntüye göre çok daha azdır. Diferansiyel analiz, aynı gizli anahtarlar kullanılmasına rağmen yöntemin düz görüntüdeki çok küçük değişikliklere duyarlı olduğunu göstermektedir.

References

  • Güvenoğlu, E., Resim Şifreleme Amacıyla Dinamik S Kutusu Tasarımı İçin Bir Yöntem, El-Cezeri Journal of Science and Engineering, 2016, 3(2): 179-191.
  • Li, Y., Wang, C., and Chen, H., A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation, Optics and Lasers in Engineering, 2017, 90, 238-246.
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  • Kaur, M., Kumar, V., A Comprehensive Review on Image Encryption Techniques, Archives of Computational Methods in Engineering, 2020, 27 (1), 15-43.
  • Kumar, M., Saxena, A., and Vuppala, S. S., Survey on Chaos Based Image Encryption Techniques, In Multimedia Security Using Chaotic Maps: Principles and Methodologies, Springer, Cham, 2020, 1-26.
  • Pareek, N. K., Patidar, V., and Sud, K. K., Image Encryption Using Chaotic Logistic Map, Image and Vision Computing, 2006, 24(9): 926-934.
  • Ye, G., Image Scrambling Encryption Algorithm of Pixel Bit Based on Chaos Map, Pattern Recognition Letters, 2010, 31(5): 347-354.
  • Ismail, S. M., Said, L. A., Radwan, A. G., Madian, A. H., and Abu-Elyazeed, M. F., Generalized Double-Humped Logistic Map-Based Medical Image Encryption, Journal of Advanced Research, 2018, 10, 85-98.
  • Li, C., Luo, G., Qin, K., and Li, C., An Image Encryption Scheme Based on Chaotic Tent Map, Nonlinear Dynamics, 2017, 87(1): 127-133.
  • Naskar, P. K., Bhattacharyya, S., Nandy, D., and Chaudhuri, A., A Robust Image Encryption Scheme Using Chaotic Tent Map and Cellular Automata, Nonlinear Dynamics, 2020, 100(3): 2877-2898.
  • Hua, Z., Zhou, Y., Image Encryption Using 2D Logistic-Adjusted-Sine map, Information Sciences, 2016, 339, 237-253.
  • Zheng, J., Liu, L., Novel Image Encryption by Combining Dynamic DNA Sequence Encryption and The Improved 2D Logistic Sine Map, IET Image Processing, 2020, 14(11): 2310-2320.
  • Ping, P., Xu, F., Mao, Y., and Wang, Z., Designing Permutation–Substitution Image Encryption Networks with Henon Map, Neurocomputing, 2018, 283, 53-63.
  • Ibrahim, S., Alharbi, A., Efficient Image Encryption Scheme Using Henon Map, Dynamic S-Boxes and Elliptic Curve Cryptography, IEEE Access, 2020, 8, 194289-194302.
  • Abbas, N. A., Image Encryption Based on Independent Component Analysis and Arnold’s Cat Map, Egyptian Informatics Journal, 2016, 17(1): 139-146.
  • Hariyanto, E., Rahim, R., Arnold’s Cat Map Algorithm in Digital Image Encryption, International Journal of Science and Research, 2016, 5(10): 1363-1365.
  • Parida, R. R., Singh, B. K., and Pradhan, C., A Novel Approach for Image Encryption Using Zaslavskii Map and Arnold’s Cat Map, In Data Engineering and Intelligent Computing, Springer, Singapore, 2021, 269-282.
  • Salleh, M., Ibrahim, S., and Isnin, I. F., Enhanced Chaotic Image Encryption Algorithm Based on Baker's Map, In Proceedings of the 2003 International Symposium on Circuits and Systems, IEEE, ISCAS’03, 2003.
  • Stoyanov, B., Kordov, K., Image Encryption Using Chebyshev Map and Rotation Equation, Entropy, 2015, 17(4): 2117-2139.
  • Liu, L., Jiang, D., Wang, X., Rong, X., and Zhang, R., 2D Logistic-Adjusted-Chebyshev Map for Visual Color Image Encryption, Journal of Information Security and Applications, 2021, 60, 102854.
  • Khan, M., Shah, T., A Literature Review on Image Encryption Techniques, 3D Research, 2014, 5(4): 1-25.
  • Mirzaei, O., Yaghoobi, M., Irani, H., A New Image Encryption Method: Parallel Sub-image encryption with hyper chaos, Nonlinear Dynamics, 2012, 67, 557-566.
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  • Zhu, Z. L., Zhang, W., Wong, K. W., and Yu, H., A Chaos-Based Symmetric Image Encryption Scheme Using a Bit-Level Permutation, Information Sciences, 2011, 181(6): 1171-1186.
  • Karawia, A. A., Elmasry, Y. A., New Encryption Algorithm Using Bit-Level Permutation and Non-Invertible Chaotic Map, IEEE Access, 2021, 9, 101357-101368.
  • Wong, K. W., Kwok, B. S. H., and Yuen, C. H., An Efficient Diffusion Approach for Chaos-Based Image Encryption, Chaos, Solitons & Fractals, 2009, 41(5): 2652-2663.
  • Alvarez, G., Li, S., Some Basic Cryptographic Requirements for Chaos-Based Cryptosystems, International Journal of Bifurcation and Chaos, 2006, 16(08): 2129-2151.
  • Shahna, K. U., Mohamed, A., A Novel Image Encryption Scheme Using Both Pixel Level and Bit Level Permutation with Chaotic Map, Applied Soft Computing, 2020, 90, 106162.
  • Shah, A. A., Parah, S. A., Rashid, M., and Elhoseny, M., Efficient Image Encryption Scheme Based on Generalized Logistic Map For Real Time Image Processing, Journal of Real-Time Image Processing, 2020, 17(6): 2139-2151.
  • Kari, A. P., Navin, A. H., Bidgoli, A. M., and Mirnia, M., A New Image Encryption Scheme Based on Hybrid Chaotic Maps, Multimedia Tools and Applications, 2021, 80(2): 2753-2772.
  • Wu, Y., Noonan, J. P., and Agaian, S., NPCR and UACI Randomness Tests for Image Encryption, Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), 2011, 1(2): 31-38.
  • Zhang, G., Ding, W., and Li, L., Image Encryption Algorithm Based on Tent Delay-Sine Cascade with Logistic Map, Symmetry, 2020, 12(3): 355.
  • Wang, X., Chen, S., and Zhang, Y., A Chaotic Image Encryption Algorithm Based on Random Dynamic Mixing, Optics & Laser Technology, 2021, 138, 106837.
  • Shengtao, G., Tao, W., Shida, W., Xuncai, Z., and Ying, N., A Novel Image Encryption Algorithm Based on Chaotic Sequences and Cross-Diffusion of Bits, IEEE Photonics Journal, 2020, 13(1): 1-15.
  • Kaur, M., Singh, D., Sun, K., and Rawat, U., Color Image Encryption Using Non-Dominated Sorting Genetic Algorithm with Local Chaotic Search Based 5D Chaotic Map, Future Generation Computer Systems, 2020, 107, 333-350.

An Image Encryption Method by Sub-image Shuffling, Bit-level Permutation and Diffusion using Chaotic Maps

Year 2022, Volume: 9 Issue: 2, 708 - 720, 31.05.2022
https://doi.org/10.31202/ecjse.995766

Abstract

Transmission of images securely through a channel can be ensured using cryptography techniques. Encrypting an image with the help of chaotic maps provides security and authentication. This paper presents an image encryption method which consists of three main steps: Sub-image shuffling, bit-level permutation, and diffusion. The sub-image shuffling step is performed using a logistic map to increase the robustness of the proposed method. In the bit-level permutation process, highest four bits of each pixel are obtained. The bit-level row and column transformations are applied using the sequences generated by a chaotic tent map. Finally, in the diffusion step, the values of the image’s pixels are altered. Two different chaotic sequences which are obtained from the logistic map and tent map are employed. Five different parameters are selected as the secret keys for the encryption. The performance of the suggested method is tested with several analysis methods. Key space analysis shows that the proposed method can withstand brute force attacks. It is also proven that the method is highly sensitive to the secret keys. Histogram analysis illustrates the fact that the encrypted image’s pixels are uniformly distributed. Also, the correlation between the neighboring pixels is reduced in the encrypted image compared to the plain image. The differential analysis demonstrates that the method is sensitive to the slight changes in the plain image even though the same secret keys are used.

References

  • Güvenoğlu, E., Resim Şifreleme Amacıyla Dinamik S Kutusu Tasarımı İçin Bir Yöntem, El-Cezeri Journal of Science and Engineering, 2016, 3(2): 179-191.
  • Li, Y., Wang, C., and Chen, H., A hyper-chaos-based image encryption algorithm using pixel-level permutation and bit-level permutation, Optics and Lasers in Engineering, 2017, 90, 238-246.
  • Muthu, J. S., Murali P., Review of Chaos Detection Techniques Performed on Chaotic Maps and Systems in Image Encryption, SN Computer Science, 2021, 2(5): 1-24.
  • Kaur, M., Kumar, V., A Comprehensive Review on Image Encryption Techniques, Archives of Computational Methods in Engineering, 2020, 27 (1), 15-43.
  • Kumar, M., Saxena, A., and Vuppala, S. S., Survey on Chaos Based Image Encryption Techniques, In Multimedia Security Using Chaotic Maps: Principles and Methodologies, Springer, Cham, 2020, 1-26.
  • Pareek, N. K., Patidar, V., and Sud, K. K., Image Encryption Using Chaotic Logistic Map, Image and Vision Computing, 2006, 24(9): 926-934.
  • Ye, G., Image Scrambling Encryption Algorithm of Pixel Bit Based on Chaos Map, Pattern Recognition Letters, 2010, 31(5): 347-354.
  • Ismail, S. M., Said, L. A., Radwan, A. G., Madian, A. H., and Abu-Elyazeed, M. F., Generalized Double-Humped Logistic Map-Based Medical Image Encryption, Journal of Advanced Research, 2018, 10, 85-98.
  • Li, C., Luo, G., Qin, K., and Li, C., An Image Encryption Scheme Based on Chaotic Tent Map, Nonlinear Dynamics, 2017, 87(1): 127-133.
  • Naskar, P. K., Bhattacharyya, S., Nandy, D., and Chaudhuri, A., A Robust Image Encryption Scheme Using Chaotic Tent Map and Cellular Automata, Nonlinear Dynamics, 2020, 100(3): 2877-2898.
  • Hua, Z., Zhou, Y., Image Encryption Using 2D Logistic-Adjusted-Sine map, Information Sciences, 2016, 339, 237-253.
  • Zheng, J., Liu, L., Novel Image Encryption by Combining Dynamic DNA Sequence Encryption and The Improved 2D Logistic Sine Map, IET Image Processing, 2020, 14(11): 2310-2320.
  • Ping, P., Xu, F., Mao, Y., and Wang, Z., Designing Permutation–Substitution Image Encryption Networks with Henon Map, Neurocomputing, 2018, 283, 53-63.
  • Ibrahim, S., Alharbi, A., Efficient Image Encryption Scheme Using Henon Map, Dynamic S-Boxes and Elliptic Curve Cryptography, IEEE Access, 2020, 8, 194289-194302.
  • Abbas, N. A., Image Encryption Based on Independent Component Analysis and Arnold’s Cat Map, Egyptian Informatics Journal, 2016, 17(1): 139-146.
  • Hariyanto, E., Rahim, R., Arnold’s Cat Map Algorithm in Digital Image Encryption, International Journal of Science and Research, 2016, 5(10): 1363-1365.
  • Parida, R. R., Singh, B. K., and Pradhan, C., A Novel Approach for Image Encryption Using Zaslavskii Map and Arnold’s Cat Map, In Data Engineering and Intelligent Computing, Springer, Singapore, 2021, 269-282.
  • Salleh, M., Ibrahim, S., and Isnin, I. F., Enhanced Chaotic Image Encryption Algorithm Based on Baker's Map, In Proceedings of the 2003 International Symposium on Circuits and Systems, IEEE, ISCAS’03, 2003.
  • Stoyanov, B., Kordov, K., Image Encryption Using Chebyshev Map and Rotation Equation, Entropy, 2015, 17(4): 2117-2139.
  • Liu, L., Jiang, D., Wang, X., Rong, X., and Zhang, R., 2D Logistic-Adjusted-Chebyshev Map for Visual Color Image Encryption, Journal of Information Security and Applications, 2021, 60, 102854.
  • Khan, M., Shah, T., A Literature Review on Image Encryption Techniques, 3D Research, 2014, 5(4): 1-25.
  • Mirzaei, O., Yaghoobi, M., Irani, H., A New Image Encryption Method: Parallel Sub-image encryption with hyper chaos, Nonlinear Dynamics, 2012, 67, 557-566.
  • Li, Y., Wang, C., and Chen, H., A Hyper-Chaos-Based Image Encryption Algorithm Using Pixel-Level Permutation and Bit-Level Permutation, Optics and Lasers in Engineering, 2017, 90, 238-246.
  • Zhu, Z. L., Zhang, W., Wong, K. W., and Yu, H., A Chaos-Based Symmetric Image Encryption Scheme Using a Bit-Level Permutation, Information Sciences, 2011, 181(6): 1171-1186.
  • Karawia, A. A., Elmasry, Y. A., New Encryption Algorithm Using Bit-Level Permutation and Non-Invertible Chaotic Map, IEEE Access, 2021, 9, 101357-101368.
  • Wong, K. W., Kwok, B. S. H., and Yuen, C. H., An Efficient Diffusion Approach for Chaos-Based Image Encryption, Chaos, Solitons & Fractals, 2009, 41(5): 2652-2663.
  • Alvarez, G., Li, S., Some Basic Cryptographic Requirements for Chaos-Based Cryptosystems, International Journal of Bifurcation and Chaos, 2006, 16(08): 2129-2151.
  • Shahna, K. U., Mohamed, A., A Novel Image Encryption Scheme Using Both Pixel Level and Bit Level Permutation with Chaotic Map, Applied Soft Computing, 2020, 90, 106162.
  • Shah, A. A., Parah, S. A., Rashid, M., and Elhoseny, M., Efficient Image Encryption Scheme Based on Generalized Logistic Map For Real Time Image Processing, Journal of Real-Time Image Processing, 2020, 17(6): 2139-2151.
  • Kari, A. P., Navin, A. H., Bidgoli, A. M., and Mirnia, M., A New Image Encryption Scheme Based on Hybrid Chaotic Maps, Multimedia Tools and Applications, 2021, 80(2): 2753-2772.
  • Wu, Y., Noonan, J. P., and Agaian, S., NPCR and UACI Randomness Tests for Image Encryption, Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), 2011, 1(2): 31-38.
  • Zhang, G., Ding, W., and Li, L., Image Encryption Algorithm Based on Tent Delay-Sine Cascade with Logistic Map, Symmetry, 2020, 12(3): 355.
  • Wang, X., Chen, S., and Zhang, Y., A Chaotic Image Encryption Algorithm Based on Random Dynamic Mixing, Optics & Laser Technology, 2021, 138, 106837.
  • Shengtao, G., Tao, W., Shida, W., Xuncai, Z., and Ying, N., A Novel Image Encryption Algorithm Based on Chaotic Sequences and Cross-Diffusion of Bits, IEEE Photonics Journal, 2020, 13(1): 1-15.
  • Kaur, M., Singh, D., Sun, K., and Rawat, U., Color Image Encryption Using Non-Dominated Sorting Genetic Algorithm with Local Chaotic Search Based 5D Chaotic Map, Future Generation Computer Systems, 2020, 107, 333-350.
There are 35 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Makaleler
Authors

Mehmet Demirtas 0000-0002-9018-3124

Publication Date May 31, 2022
Submission Date September 15, 2021
Acceptance Date November 22, 2021
Published in Issue Year 2022 Volume: 9 Issue: 2

Cite

IEEE M. Demirtas, “An Image Encryption Method by Sub-image Shuffling, Bit-level Permutation and Diffusion using Chaotic Maps”, ECJSE, vol. 9, no. 2, pp. 708–720, 2022, doi: 10.31202/ecjse.995766.