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Recent Advances in Computer Science and Communications

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ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

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General Research Article

Fast and Efficient Data Masking Method for Securing Image Over Cloud Computing Environment

Author(s): B.K. Siddartha* and G.K. Ravikumar

Volume 15, Issue 4, 2022

Published on: 02 October, 2020

Article ID: e220322186533 Pages: 13

DOI: 10.2174/2666255813999201002151500

Price: $65

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Abstract

Objective: Preserving the confidentiality of sensitive information is becoming more and more difficult and challenging, considering current scenarios, as a huge amount of multimedia data are stored and communicated over the internet among users and cloud computing environment. The existing cryptography security model for storing images on a cloud platform cannot resist various kinds of modern attacks, such as statistical, differential, brute force, cropping attack, etc., therefore, an improved bit scrambling technique using chaotic maps that can resist various kinds of security attacks is needed. The FEDM cipher image provides less correlation among neighboring pixels and images can be decrypted even under the presence of noise. This study proposed a FEDM model to achieve better UACI, NPCR, histogram, runtime, and processing time performance than the existing image security methods.

Methods: Preserving the confidentiality of sensitive information is becoming more and more difficult and challenging considering current scenarios as a huge amount of multimedia data are stored and communicated over the internet among users and cloud computing environment. The existing cryptography security model for storing images on a cloud platform cannot resist various kinds of modern attacks such as statistical, differential, brute force, cropping attack, etc.

Results: The overall results show that the proposed FEDM model attains much superior performance considering histogram, UACI, NPCR, and runtime. The FEDM model can resist against SA. The FEDM model attains better performance because IBS is used in each step of CS. Thus, a correlation between adjacent pixels is less and aids superior security performance. Further, the FEDM model attains better UACI and NPCR performance when compared with the exiting image encryption model.

Conclusion: The FEDM security method can resist DA, noise, cropping attack, and linear attacks more efficiently due to a larger keyspace. Further, the FEDM takes less time for provisioning security. Along with this, FEDM works smoothly under a cloud computing environment. No prior work has considered runtime performance evaluation under the cloud computing environment. FEDM model will significantly aid in reducing the overall operational cost of a cloud computing environment with a reduction in processing time as cloud charge is based on hours of usage.

Keywords: Cryptography, Chaotic system, DNA encoding, Data masking, Runtime complexity, FEDM.

Graphical Abstract

[1]
J. Wu, S. Guo, J. Li, and D. Zeng, "Big data meet green challenges: Big data toward green applications", IEEE Syst. J., vol. 10, no. 3, pp. 888-900, 2016.
[2]
J. Wu, S. Guo, J. Li, and D. Zeng, "Big data meet green challenges: Greening big data", IEEE Syst. J., vol. 10, no. 3, pp. 873-887, 2016.
[3]
G.J. Simmons, "Symmetric and asymmetric encryption", ACM Comput. Surv., vol. 11, no. 4, pp. 305-330, 1979.
[http://dx.doi.org/10.1145/356789.356793]
[4]
D. Ravichandran, P. Praveenkumar, J.B. Balaguru Rayappan, and R. Amirtharajan, "Chaos based crossover and mutation for securing DICOM image", Comput. Biol. Med., vol. 72, pp. 170-184, 2016.
[http://dx.doi.org/10.1016/j.compbiomed.2016.03.020] [PMID: 27046666]
[5]
D. Ravichandran, P. Praveenkumar, J.B.B. Rayappan, and R. Amirtharajan, "DNA chaos blend to secure medical privacy", IEEE Trans. Nanobioscience, vol. 16, no. 8, pp. 850-858, 2017.
[http://dx.doi.org/10.1109/TNB.2017.2780881] [PMID: 29364129]
[6]
A.A. Abd El-Latif, B. Abd-El-Atty, and M. Talha, "Robust encryption of quantum medical images", IEEE Access, vol. 6, pp. 1073-1081, 2018.
[http://dx.doi.org/10.1109/ACCESS.2017.2777869]
[7]
L. Huang, S. Cai, X. Xiong, and M. Xiao, "On symmetric color image encryption system with permutation-diffusion simultaneous operation", Opt. Lasers Eng., vol. 115, pp. 7-20, 2019.
[http://dx.doi.org/10.1016/j.optlaseng.2018.11.015]
[8]
Y. Luo, S. Tang, X. Qin, L. Cao, F. Jiang, and J. Liu, "A double image encryption scheme based on amplitude-phase encoding and discrete complex random transformation", IEEE Access, vol. 6, pp. 77740-77753, 2018.
[http://dx.doi.org/10.1109/ACCESS.2018.2884013]
[9]
C. Zhu, and K. Sun, "Cryptanalyzing and improving a novel color image encryption algorithm using RT-enhanced chaotic tent maps", IEEE Access, vol. 6, pp. 18759-18770, 2018.
[http://dx.doi.org/10.1109/ACCESS.2018.2817600]
[10]
N. Koblitiz, "Elliptic curve cryptosystems", Math. Comput., vol. 48, no. 177, pp. 203-208, 1987.
[http://dx.doi.org/10.1090/S0025-5718-1987-0866109-5]
[11]
Z. Liu, T. Xia, and J. Wang, "Image encryption technique based on new two-dimensional fractional-order discrete chaotic map and Menezes-Vanstone elliptic curve cryptosystem", Chin. Phys. B, vol. 27, no. 3, pp. 1-16, 2018.
[12]
M. Kumar, A. Iqbal, and P. Kumar, "A new RGB image encryption algorithm based on DNA encoding and elliptic curve Diffie-Hellman cryptography", Signal Processing, vol. 125, pp. 187-202, 2016.
[http://dx.doi.org/10.1016/j.sigpro.2016.01.017]
[13]
A Ayoup, A Hussein, and M Attia, "Efficient selective image encryption", Multimed. Tools Appl., Springer Science+Business Media New York, .
[http://dx.doi.org/10.1007/s11042-015-2985-7]
[14]
M. Ahmad, U. Shamsi, and I. Khan, "An enhanced image encryption algorithm using fractional chaotic systems", Procedia Comput. Sci., vol. 57, pp. 852-859, 2015.
[http://dx.doi.org/10.1016/j.procs.2015.07.494]
[15]
J. Chandrasekaran, and S.J. Thiruvengadam, "A hybrid chaotic and number theoretic approach for securing DICOM images", Secur. Commun. Netw., vol. 2017, pp. 1-12, 2017.https://www.hindawi.com/journals/scn/2017/6729896/
[http://dx.doi.org/10.1155/2017/6729896]
[16]
X. Chai, Z. Gan, K. Yuan, Y. Chen, and X. Liu, "A novel image encryption scheme based on DNA sequence operations and chaotic systems", Neural Comput. Appl., vol. 31, no. 1, pp. 219-237, 2019.https://link.springer.com/article/10.1007/s00521-017-2993-9
[17]
X. Wang, and C. Liu, "A novel and effective image encryption algorithm based on chaos and DNA encoding", Multimedia Tools Appl., vol. 76, no. 5, pp. 6229-6245, 2017.
[http://dx.doi.org/10.1007/s11042-016-3311-8]
[18]
X. Wang, Y. Zhang, and Y. Zhao, "A novel image encryption scheme based on 2-D logistic map and DNA sequence operations", Nonlinear Dyn., vol. 82, no. 3, pp. 1269-1280, 2015.
[http://dx.doi.org/10.1007/s11071-015-2234-7]
[19]
A. Rehman, X. Liao, A. Kulsoom, and S.A. Abbas, "Selective encryption for gray images based on chaos and DNA complementary rules", Multimedia Tools Appl., vol. 74, no. 13, pp. 4655-4677, 2015.
[http://dx.doi.org/10.1007/s11042-013-1828-7]
[20]
A. Jain, and N. Rajpal, "A robust image encryption algorithm resistant to attacks using DNA and chaotic logistic maps", Multimedia Tools Appl., vol. 75, no. 10, pp. 5455-5472, 2016.
[http://dx.doi.org/10.1007/s11042-015-2515-7]
[21]
X. Wang, Y. Zhang, and X. Bao, "A novel chaotic image encryption scheme using DNA sequence operations", Opt. Lasers Eng., vol. 73, pp. 53-61, 2015.
[http://dx.doi.org/10.1016/j.optlaseng.2015.03.022]
[22]
X. Zhang, Z. Zhou, and Y. Niu, "An Image Encryption Method Based on the Feistel Network and Dynamic DNA Encoding", IEEE Photonics J., vol. 10, no. 4, pp. 1-14, 2018.
[http://dx.doi.org/10.1109/JPHOT.2018.2859257]
[23]
S. Sun, "A novel hyperchaotic image encryption scheme based on DNA encoding, pixel-level scrambling and bit-level scrambling", IEEE Photonics J., vol. 10, no. 2, pp. 1-14, 2018.
[http://dx.doi.org/10.1109/JPHOT.2018.2817550]
[24]
Haiju. Fan, and M. Li, "Cryptanalysis and improvement of chaos-based image encryption scheme with circular inter-intra-pixels bit-level permutation", Math. Probl. Eng., vol. 2017, pp. 1-11, 2017.
[http://dx.doi.org/10.1155/2017/8124912]
[25]
A. Kanso, and M. Ghebleh, "An efficient and robust image encryption scheme for medical applications", Commun. Nonlinear Sci. Numer. Simul., vol. 24, no. 1–3, pp. 98-116, 2015.
[http://dx.doi.org/10.1016/j.cnsns.2014.12.005]
[26]
K. Muhammad, M. Sajjad, I. Mehmood, S. Rho, and S.W. Baik, "A novel magic LSB substitution method (M-LSB-SM) using multi-level encryptionand achromatic component of an image", Multimedia Tools Appl., vol. 75, no. 22, pp. 14867-14893, 2016.
[http://dx.doi.org/10.1007/s11042-015-2671-9]
[27]
X. Fu, B. Liu, Y. Xie, W. Li, and Y. Liu, "Image encryption-then-transmission using DNA encryption algorithm and the double chaos", IEEE Photonics J., vol. 10, no. 3, pp. 1-15, 2018.
[http://dx.doi.org/10.1109/JPHOT.2018.2827165]
[28]
"Standard Test Images", Michigan--ww.ece.rice.edu/~wakin/images/
[29]
X. Wang, L. Teng, and X. Qin, "A novel color image encryption algorithm based on chaos", Signal Processing, vol. 92, no. 4, pp. 1101-1108, 2012.
[http://dx.doi.org/10.1016/j.sigpro.2011.10.023]
[30]
L. Xu, Z. Li, J. Li, and W. Hua, "A novel bit-level image encryption algorithm based on chaotic maps", Opt. Lasers Eng., vol. 78, no. 21, pp. 17-25, 2016.
[http://dx.doi.org/10.1016/j.optlaseng.2015.09.007]
[31]
L-C. Huang, L-Y. Tseng, and M-S. Hwang, "A reversible data hiding method by histogram shifting in high quality medical images", J. Syst. Softw., vol. 86, no. 3, pp. 716-727, 2013.
[http://dx.doi.org/10.1016/j.jss.2012.11.024]
[32]
R-F. Liao, "Security enhancement for mobile edge computing through physical layer authentication", IEEE Access, vol. 7, pp. 116390-116401, 2019.
[http://dx.doi.org/10.1109/ACCESS.2019.2934122]
[33]
R. Atat, L. Liu, H. Chen, J. Wu, H. Li, and Y. Yi, "“Enabling cyber-physical communication in 5g cellular networks: challenges, spatial spectrum sensing, and cyber-security”, IET Cyber-Phys", Syst. Theory Appl., vol. 2, no. 1, pp. 49-54, 2017.
[http://dx.doi.org/10.1049/iet-cps.2017.0010]
[34]
R. Atat, L. Liu, J. Wu, G. Li, C. Ye, and Y. Yang, "Big data meet cyber-physical systems: A panoramic survey", IEEE Access, vol. 6, pp. 73603-73636, 2018.
[http://dx.doi.org/10.1109/ACCESS.2018.2878681]
[35]
Y. Luo, R. Zhou, J. Liu, C. Yi, and X. Ding, "A parallel image encryption algorithm based on the piecewise linear chaotic map and hyper-chaotic map", Nonlinear Dyn., vol. 93, no. 3, pp. 1165-1181, 2018.
[http://dx.doi.org/10.1007/s11071-018-4251-9]
[36]
Y. Luo, R. Zhou, J. Liu, S. Qiu, and C. Yi, "An efficient and self-adapting color-image encryption algorithm based on chaos and interactions among multiple layers", Multimedia Tools Appl., vol. 77, pp. 26191-26217, 2018.
[37]
Z. Zhang, and W-C. Hong, "Electric load forecasting by complete ensemble empirical model decomposition adaptive noise and support vector regression with quantum-based dragonfly algorithm", Nonlinear Dyn., vol. 98, pp. 1107-1136, 2019.
[http://dx.doi.org/10.1007/s11071-019-05252-7]
[38]
Z. Zhang, S. Ding, and Y. Sun, "A support vector regression model hybridized with chaotic krill herd algorithm and empirical mode decomposition for regression task", Neurocomputing, vol. 410, pp. 185-201, 2020.
[http://dx.doi.org/10.1016/j.neucom.2020.05.075]

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