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Towards Integrating Image Encryption with Compression: A Survey

Published:04 March 2022Publication History
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Abstract

As digital images are consistently generated and transmitted online, the unauthorized utilization of these images is an increasing concern that has a significant impact on both security and privacy issues; additionally, the representation of digital images requires a large amount of data. In recent years, an image compression scheme has been widely considered; such a scheme saves on hardware storage space and lowers both the transmission time and bandwidth demand for various potential applications. In this article, we review the various approaches taken to consider joint encryption and compression, assessing both their merits and their limitations. In addition to the survey, we also briefly introduce the most interesting and most often utilized applications of image encryption and evaluation metrics, providing an overview of the various kinds of image encryption schemes available. The contribution made by these approaches is then summarized and compared, offering a consideration of the different technical perspectives. Lastly, we highlight the recent challenges and some potential research directions that could fill the gaps in these domains for both researchers and developers.

REFERENCES

  1. [1] Sun W., Zhou J., Li Y., Cheung M., and She J.. 2021. Robust high-capacity watermarking over online social network shared images. IEEE Transactions on Circuits and Systems for Video Technology 31, 3 (2021), 12081221.Google ScholarGoogle ScholarCross RefCross Ref
  2. [2] Mahato S., Yadav D., and Khan D.. 2019. A novel information hiding scheme based on social networking site viewers’ public comments. Journal of Information Security and Applications 47 (2019), 275283.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. [3] Osman M.. 2021. Wild and interesting Facebook statistics and facts. Retrieved from https://kinsta.com/blog/facebook-statistics/.Google ScholarGoogle Scholar
  4. [4] Systrom K.. 2021. Instagram by the numbers: Stats, demographics & fun facts. Retrieved from https://www.omnicoreagency.com/instagram-statistics/.Google ScholarGoogle Scholar
  5. [5] Smith C.. 2021. Flickr statistics, user count and facts. Retrieved from https://expandedramblings.com/index.php/flickr-stats/.Google ScholarGoogle Scholar
  6. [6] Quicksprout. 2019. How to increase Twitter engagement by 324%. Retrieved from https://www.quicksprout.com/twitter-engagement/.Google ScholarGoogle Scholar
  7. [7] Gupta B. B., Yamaguchi S., and Agrawal D. P.. 2018. Advances in security and privacy of multimedia big data in mobile and cloud computing. Multimedia Tools and Applications 77, 7 (2018), 92039208.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. [8] Zhou X. Q., Huang H. K., and Lou S. L.. 2001. Authenticity and integrity of digital mammography images. IEEE Transactions on Medical Imaging 20, 8 (2001), 784791.Google ScholarGoogle ScholarCross RefCross Ref
  9. [9] Haddad S., Coatrieux G., Moreau-Gaudry A., and Cozic M.. 2020. Joint watermarking-encryption-JPEG-LS for medical image reliability control in encrypted and compressed domains. IEEE Transactions on Information Forensics and Security 15 (2020), 25562569.Google ScholarGoogle ScholarCross RefCross Ref
  10. [10] Singh A. K. and Mohan A.. 2019. Handbook of Multimedia Information Security: Techniques and Applications. Springer International Publishing.Google ScholarGoogle ScholarCross RefCross Ref
  11. [11] Swaminathan A., Mao Yinian, and Wu Min. 2006. Robust and secure image hashing. IEEE Transactions on Information Forensics and Security 1, 2 (2006), 215230.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. [12] Schneier B.. 2015. Applied Cryptography: Protocols, Algorithms and Source Code in C. John Wiley & Sons.Google ScholarGoogle Scholar
  13. [13] Li Y., Yu H., Song B., and Chen J.. 2021. Image encryption based on a single-round dictionary and chaotic sequences in cloud computing. Concurrency and Computation: Practice and Experience 33, 7 (2021), 1.Google ScholarGoogle ScholarCross RefCross Ref
  14. [14] Liu H., Zhao B., and Huang L.. 2019. A remote-sensing image encryption scheme using DNA bases probability and two-dimensional logistic map. IEEE Access 7 (2019), 6545065459.Google ScholarGoogle ScholarCross RefCross Ref
  15. [15] Li Y., Song B., Cao R., Zhang Y., and Qin H.. 2016. Image encryption based on compressive sensing and scrambled index for secure multimedia transmission. ACM Transactions on Multimedia Computing, Communications, and Applications 12, 4 (2016), 122.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. [16] Asgari-Chenaghlu Meysam, Feizi-Derakhshi Mohammad-Reza, Nikzad-Khasmakhi Narjes, Feizi-Derakhshi Ali-Reza, Ramezani Majid, Jahanbakhsh-Nagadeh Zoleikha, Rahkar-Farshi Taymaz, Zafarani-Moattar Elnaz, Ranjbar-Khadivi Mehrdad, and Balafar. Mohammad-Ali 2021. Cy: Chaotic yolo for user intended image encryption and sharing in social media. Information Sciences 542 (2021), 212227.Google ScholarGoogle ScholarCross RefCross Ref
  17. [17] Kumar S., Panna B., and Jha R. K.. 2019. Medical image encryption using fractional discrete cosine transform with chaotic function. Medical & Biological Engineering & Computing 57 (2019), 25172533.Google ScholarGoogle ScholarCross RefCross Ref
  18. [18] Muhammad K., Hamza R., Ahmad J., Lloret J., Wang H., and Baik S. W.. 2018. Secure surveillance framework for IoT systems using probabilistic image encryption. IEEE Transactions on Industrial Informatics 14, 8 (2018), 36793689.Google ScholarGoogle ScholarCross RefCross Ref
  19. [19] Dang P. P. and Chau P. M.. 2000. Image encryption for secure internet multimedia applications. IEEE Transactions on Consumer Electronics 46, 3 (2000), 395403.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. [20] Preishuber M., Hütter T., Katzenbeisser S., and Uhl A.. 2018. Depreciating motivation and empirical security analysis of chaos-based image and video encryption. IEEE Transactions on Information Forensics and Security 13, 9 (2018), 21372150.Google ScholarGoogle ScholarCross RefCross Ref
  21. [21] Shamama Anwar and Meghana Solleti. 2019. A pixel permutation based image encryption technique using chaotic map. Multimedia Tools and Applications 78, 19 (2019), 2756927590.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. [22] Ying Niu and Zhang Xuncai. 2020. A novel plaintext-related image encryption scheme based on chaotic system and pixel permutation. IEEE Access 8 (2020), 2208222093.Google ScholarGoogle ScholarCross RefCross Ref
  23. [23] Thoms G. R. W., Muresan R., and Al-Dweik A.. 2019. Chaotic encryption algorithm with key controlled neural networks for intelligent transportation systems. IEEE Access 7 (2019), 158697158709.Google ScholarGoogle ScholarCross RefCross Ref
  24. [24] Singh H.. 2016. Cryptosystem for securing image encryption using structured phase masks in fresnel wavelet transform domain. 3D Research 7, 34 (2016), 1--18.Google ScholarGoogle Scholar
  25. [25] Shafique A. and Ahmed F.. 2020. Image encryption using dynamic S-box substitution in the wavelet domain. Wireless Personal Communications 115 (2020). 22432268.Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. [26] Lima J. B., Madeiro F., and Sales F.. 2015. Encryption of medical images based on the cosine number transform. Signal Processing: Image Communication 35 (2015), 18.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. [27] Huang W., Jiang D., An Y., Liu L., and Wang X.. 2021. A novel double-image encryption algorithm based on rossler hyperchaotic system and compressive sensing. IEEE Access 9 (2021), 4170441716.Google ScholarGoogle ScholarCross RefCross Ref
  28. [28] Huo D., Zhu X., Dai G., Yang H., Zhou X., and Feng M.. 2020. Novel image compression–encryption hybrid scheme based on DNA encoding and compressive sensing. Applied Physics B 126, 3 (2020), 45.Google ScholarGoogle ScholarCross RefCross Ref
  29. [29] Cambareri V., Mangia M., Pareschi F., Rovatti R., and Setti G.. 2015. On known-plaintext attacks to a compressed sensing-based encryption: A quantitative analysis. IEEE Transactions on Information Forensics and Security 10, 10 (2015), 21822195.Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. [30] Song Jaehun and Ho Lee Yeon. 2021. Optical image encryption using different twiddle factors in the butterfly algorithm of fast Fourier transform. Optics Communications 485 (2021), 126707.Google ScholarGoogle ScholarCross RefCross Ref
  31. [31] Sun W., Wang L., Wang J., Li H., and Wu Q.. 2018. Optical image encryption using gamma distribution phase masks in the gyrator domain. Journal of the European Optical Society Rapid Publications 14, 28 (2018), 1--10.Google ScholarGoogle Scholar
  32. [32] Chai X., Bi J., Gan Z., Liu X., Zhang Y., and Chen Y.. 2020. Color image compression and encryption scheme based on compressive sensing and double random encryption strategy. Signal Processing 176 (2020), 107684.Google ScholarGoogle ScholarCross RefCross Ref
  33. [33] Tong X. J., Zhang M., Wang Z., and Ma J.. 2016. A joint color image encryption and compression scheme based on hyper-chaotic system. Nonlinear Dynamics 84, 4 (2016), 23332356.Google ScholarGoogle ScholarCross RefCross Ref
  34. [34] Uthayakumar J., Vengattaraman T., and Dhavachelvan P.. 2021. A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications. Journal of King Saud University - Computer and Information Sciences 33, 2 (2021), 119140.Google ScholarGoogle ScholarCross RefCross Ref
  35. [35] Hussain A. J., Al-Fayadh Ali, and Radi Naeem. 2018. Image compression techniques: A survey in lossless and lossy algorithms. Neurocomputing 300 (2018), 4469.Google ScholarGoogle ScholarCross RefCross Ref
  36. [36] Zhou N., Pan S., Cheng S., and Zhou Z.. 2016. Image compression–encryption scheme based on hyper-chaotic system and 2D compressive sensing. Optics & Laser Technology 82 (2016), 121133.Google ScholarGoogle ScholarCross RefCross Ref
  37. [37] Mahendiran N. and Deepa C.. 2021. A comprehensive analysis on image encryption and compression techniques with the assessment of performance evaluation metrics. SN Computer Science 2, 29 (2021), 1--12.Google ScholarGoogle Scholar
  38. [38] Zhang X., Zhu G., and Ma S.. 2012. Remote-sensing image encryption in hybrid domain. Optics Communications 285, 7 (2012), 17361743.Google ScholarGoogle ScholarCross RefCross Ref
  39. [39] Guan M., Yang X., and Hu W.. 2019. Chaotic image encryption algorithm using frequency-domain DNA encoding. IET Image Processing 13, 9 (2019), 15351539.Google ScholarGoogle ScholarCross RefCross Ref
  40. [40] Zhang Y., Zhang L. Y., Zhou J., Liu L., Chen F., and He X.. 2016. A review of compressive sensing in information security field. IEEE Access 4 (2016), 25072519.Google ScholarGoogle ScholarCross RefCross Ref
  41. [41] Chen H., Du X., Liu Z., and Yang C.. 2013. Color image encryption based on the affine transform and gyrator transform. Optics and Lasers in Engineering 51, 6 (2013), 768775.Google ScholarGoogle ScholarCross RefCross Ref
  42. [42] Wu Y., Noonan J. P., and Agaian S.. 2011. NPCR and UACI randomness tests for image encryption. Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications 1, 2 (2011), 3138.Google ScholarGoogle Scholar
  43. [43] Gan Z., Bi J., Ding W., and Chai X.. 2021. Exploiting 2D compressed sensing and information entropy for secure color image compression and encryption. Neural Computing & Applications 33 (2021), 1284512867.Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. [44] Mehra I. and Nishchal N. K.. 2015. Optical asymmetric image encryption using gyrator wavelet transform. Optics Communications 354 (2015), 344352.Google ScholarGoogle ScholarCross RefCross Ref
  45. [45] Abbas Nidaa AbdulMohsin. 2016. Image encryption based on independent component analysis and Arnold's cat map. Egyptian Informatics Journal 17, 1 (2016), 139146.Google ScholarGoogle ScholarCross RefCross Ref
  46. [46] Mohamed Faraoun Kamel. 2014. A parallel block-based encryption schema for digital images using reversible cellular automata. Engineering Science and Technology, an International Journal 17, 2 (2014), 8594.Google ScholarGoogle ScholarCross RefCross Ref
  47. [47] Martín del Rey A., Rodríguez Sánchez G., and de la Villa Cuenca A.. 2015. A protocol to encrypt digital images using chaotic maps and memory cellular automata. Logic Journal of the IGPL 23, 3 (2015), 485494.Google ScholarGoogle ScholarCross RefCross Ref
  48. [48] Yao Lili, Yuan Caojin, Qiang Junjie, Feng Shaotong, and Nie Shouping. 2017. An asymmetric color image encryption method by using deduced gyrator transform. Optics and Lasers in Engineering 89 (2017), 7279.Google ScholarGoogle ScholarCross RefCross Ref
  49. [49] Srivastava G., Vinoth Kumar C. N. S., Kavitha V., Parthiban N., and Venkataraman R.. 2020. Two-stage data encryption using chaotic neural networks. Journal of Intelligent & Fuzzy Systems 38, 3 (2020), 25612568.Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. [50] Sun Y., Xu R., Chen L., and Hu X.. 2015. Image compression and encryption scheme using fractal dictionary and Julia set. IET Image Processing 9, 3 (2015), 173183.Google ScholarGoogle ScholarCross RefCross Ref
  51. [51] Minemura K., Wong K., Qi X., and Tanaka K.. 2017. A scrambling framework for block transform compressed image. Multimedia Tools and Applications 76, 5 (2017), 67096729.Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. [52] Li X., Xiao D., Mou H., Lu D., and Peng M.. 2020. A compressive sensing based image encryption and compression algorithm with identity authentication and blind signcryption. IEEE Access 8 (2020), 211676211690.Google ScholarGoogle ScholarCross RefCross Ref
  53. [53] Yang F., Mou J., Sun K., and Chu R.. 2020. Lossless image compression-encryption algorithm based on BP neural network and chaotic system. Multimedia Tools and Applications 79, 27 (2020), 1996319992.Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. [54] Lidong L., Jiang D., Wang X., Zhang L., and Rong X.. 2020. A dynamic triple-image encryption scheme based on chaos, S-Box and image compressing. IEEE Access 8 (2020), 210382210399.Google ScholarGoogle ScholarCross RefCross Ref
  55. [55] Yu C., Li H., and Wang X.. 2019. SVD-based image compression, encryption, and identity authentication algorithm on cloud. IET Image Processing 13, 12 (2019), 22242232.Google ScholarGoogle ScholarCross RefCross Ref
  56. [56] Jiang D., Liu L., Wang X., and XRong . 2021. Image encryption algorithm for crowd data based on a new hyperchaotic system and Bernstein polynomial. IET Image Processing 15, 14 (2021), 120.Google ScholarGoogle Scholar
  57. [57] Yang F., Mou J., Sun K., Cao Y., and Jin J.. 2019. Color image compression-encryption algorithm based on fractional-order memristor chaotic circuit. IEEE Access 7 (2019), 5875158763.Google ScholarGoogle ScholarCross RefCross Ref
  58. [58] Hu H., Cao Y., Xu J., Ma C., and Yan H.. 2021. An image compression and encryption algorithm based on the fractional-order simplest chaotic circuit. IEEE Access 9 (2021), 2214122155.Google ScholarGoogle ScholarCross RefCross Ref
  59. [59] Anand A., Singh A. K., Lv Z., and Bhatnagar G.. 2020. Compression-then-encryption-based secure watermarking technique for smart healthcare system. IEEE MultiMedia 27, 4 (2020), 133143.Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. [60] Zhou J., Liu X., Au O. C., and Tang Y. Y.. 2014. Designing an efficient image encryption-then-compression system via prediction error clustering and random permutation. IEEE Transactions on Information Forensics and Security 9, 1 (2014), 3950.Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. [61] Zhang X., Ren Y., Shen L., Qian Z., and Feng G.. 2014. Compressing encrypted images with auxiliary information. IEEE Transactions on Multimedia 16, 5 (2014), 13271336.Google ScholarGoogle ScholarCross RefCross Ref
  62. [62] Wang Chuntao, Ni Jiangqun, and Huang Qiong. 2015. A new encryption-then-compression algorithm using the rate–distortion optimization. Signal Processing: Image Communication 39 (2015), 141150.Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. [63] Kurihara Kenta, Kikuchi Masanori, Imaizumi Shoko, Shiota Sayaka, and Kiya Hitoshi. 2015. An encryption-then-compression system for JPEG/Motion JPEG standard. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E98, 11 (2015), 22382245.Google ScholarGoogle ScholarCross RefCross Ref
  64. [64] Kumar Manoj and Vaish Ankita. 2017. An efficient encryption-then-compression technique for encrypted images using SVD. Digital Signal Processing 60 (2017), 8189.Google ScholarGoogle ScholarDigital LibraryDigital Library
  65. [65] Zhu S., Zhu C., and Wang W.. 2018. A novel image compression-encryption scheme based on chaos and compression sensing. IEEE Access 6 (2018), 6709567107.Google ScholarGoogle ScholarCross RefCross Ref
  66. [66] Chuman T., Sirichotedumrong W., and Kiya H.. 2019. Encryption-then-compression systems using grayscale-based image encryption for JPEG images. IEEE Transactions on Information Forensics and Security 14, 6 (2019), 15151525.Google ScholarGoogle ScholarCross RefCross Ref
  67. [67] Qin C., Zhou Q., Cao F., Dong J., and Zhang X.. 2019. Flexible lossy compression for selective encrypted image with image inpainting. IEEE Transactions on Circuits and Systems for Video Technology 29, 11 (2019), 33413355.Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. [68] Wang C., Li T., Ni J., and Huang Q.. 2020. A new MRF-based lossy compression for encrypted binary images. IEEE Access 8 (2020), 1132811341.Google ScholarGoogle ScholarCross RefCross Ref
  69. [69] Zhang B., Xiao D., and Xiang Y.. 2020. Robust coding of encrypted images via 2D compressed sensing. IEEE Transactions on Multimedia 23 (2020), 2656–267.Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. [70] Suguna T. and Shanmugalakshmi R.. 2021. Secure image communication through adaptive deer hunting optimization based vector quantization coding of perceptually encrypted images. Wireless Personal Communications 116, 3 (2021), 22392260.Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. [71] Singh K. and Kumar C.. 2020. Encryption-then-compression-based copyright protection scheme for E-Governance. IT Professional 22, 2 (2020), 4552.Google ScholarGoogle ScholarCross RefCross Ref
  72. [72] Singh A. K., Thakur S., Jolfaei Alireza, Srivastava Gautam, Elhoseny Md., and Mohan A.. 2021. Joint encryption and compression-based watermarking technique for security of digital documents. ACM Transactions on Internet Technology 21, 1 (2021), 120Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. [73] Alqaralleh B. A. Y., Vaiyapuri T., Parvathy V. S., Gupta G., Khanna A., and Shankar K.. 2021. Blockchain-assisted secure image transmission and diagnosis model on Internet of medical things environment. Personal and Ubiquitous Computing (2021), 1--11.Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. [74] Huang Xiaoling, Ye Guodong, Chai Huajin, and Xie Ou. 2015. Compression and encryption for remote sensing image using chaotic system. Security and Communication Networks 8, 18 (2015), 36593666.Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. [75] Wang Q., Chen X., Wei M., and Miao Z.. 2016. Simultaneous encryption and compression of medical images based on optimized tensor compressed sensing with 3D Lorenz. BioMedical Engineering OnLine 15, 1 (2016), 118.Google ScholarGoogle ScholarCross RefCross Ref
  76. [76] Li Peiya and Lo Kwok-Tung. 2017. Joint image compression and encryption based on order-8 alternating transforms. Journal of Visual Communication and Image Representation 44 (2017), 6171.Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. [77] Zhang Ye, Xu Biao, and Zhou Nanrun. 2017. A novel image compression–encryption hybrid algorithm based on the analysis sparse representation. Optics Communications 392 (2017), 223233.Google ScholarGoogle ScholarCross RefCross Ref
  78. [78] Li P. and Lo K.. 2018. A content-adaptive joint image compression and encryption scheme. IEEE Transactions on Multimedia 20, 8 (2018), 19601972.Google ScholarGoogle ScholarCross RefCross Ref
  79. [79] Ponuma R. and Amutha R.. 2018. Compressive sensing based image compression-encryption using novel 1D-chaotic map. Multimedia Tools and Applications 77, 15 (2018), 1920919234.Google ScholarGoogle ScholarDigital LibraryDigital Library
  80. [80] Wang Q., Wei M., Chen X., and Miao Z.. 2018. Joint encryption and compression of 3D images based on tensor compressive sensing with non-autonomous 3D chaotic system. Multimedia Tools and Applications 77, 2 (2018), 17151734.Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. [81] Duseja T. and Deshmukh M.. 2019. Image compression and encryption using Chinese remainder theorem. Multimedia Tools and Applications 78, 12 (2019), 1672716753.Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. [82] Zhang M., Tong X. J., Liu J., Wang Z., Liu J., Liu B., and Ma J.. 2020. Image compression and encryption scheme based on compressive sensing and Fourier transform. IEEE Access 8 (2020), 4083840849.Google ScholarGoogle ScholarCross RefCross Ref
  83. [83] Ghaffari A.. 2021. Image compression-encryption method based on two-dimensional sparse recovery and chaotic system. Scientific Reports 11, 1 (2021).Google ScholarGoogle ScholarCross RefCross Ref
  84. [84] Xu Y., Xiong L., Xu Z., and Pan S.. 2014. A content security protection scheme in jpeg compressed domain. Journal of Visual Communication and Image Representation 25, 5 (2014), 805813.Google ScholarGoogle ScholarCross RefCross Ref
  85. [85] Socek D., Kalva H., Magliveras S. S., Marques O., Culibrk D., and Furht B.. 2007. New approaches to encryption and steganography for digital videos. Multimedia Systems 13, 3 (2007), 191204.Google ScholarGoogle ScholarDigital LibraryDigital Library
  86. [86] Gan Z. H., Chai X. L., Han D. J., and Chen Y. R.. 2019. A chaotic image encryption algorithm based on 3-d bit-plane permutation. Neural Computing & Applications 31, 11 (2019), 71117130.Google ScholarGoogle ScholarDigital LibraryDigital Library
  87. [87] Hu J. and Han F.. 2009. A pixel-based scrambling scheme for digital medical images protection. Journal of Network and Computer Applications 32, 4 (2009), 788794.Google ScholarGoogle ScholarDigital LibraryDigital Library
  88. [88] Zhu H., Zhao C., and Zhang X.. 2013. A novel image encryption-compression scheme using hyper-chaos and Chinese remainder theorem. Signal Processing: Image Communication 28, 6 (2013), 670680.Google ScholarGoogle ScholarCross RefCross Ref
  89. [89] Tong X. J., Wang Z., Zhang M., and Liu Y.. 2013. A new algorithm of the combination of image compression and encryption technology based on cross chaotic map. Nonlinear Dynamics, 72, 1 (2013), 229241.Google ScholarGoogle ScholarCross RefCross Ref

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      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 18, Issue 3
      August 2022
      478 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/3505208
      Issue’s Table of Contents

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      Publication History

      • Published: 4 March 2022
      • Accepted: 1 November 2021
      • Revised: 1 August 2021
      • Received: 1 August 2021
      Published in tomm Volume 18, Issue 3

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