Bit operations with elements of the RSA algorithm in encryption-decryption of color images

dc.citation.epage10
dc.citation.issue3
dc.citation.journalTitleВимірювальна техніка та метрологія
dc.citation.spage5
dc.citation.volume83
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorKovalchuk, Anatoliy
dc.contributor.authorPeleckh, Yuriy
dc.contributor.authorBubela, Tetiana
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-05-09T10:30:44Z
dc.date.available2023-05-09T10:30:44Z
dc.date.created2022-02-28
dc.date.issued2022-02-28
dc.description.abstractAn image as a stochastic signal is one of the most common forms of information. Protecting images from unauthorized access and applying is a correspondingly urgent task. This causes the use of well-known classical encryption methods in the case of image encryption. But the image is a signal that possesses, in addition to typical informativeness, also visual informativeness. Informativeness for modern image processing methods makes it possible to ensure unauthorized access. Creating an attack on an encrypted image is possible in two ways: by traditional hacking of encryption methods, or by classical methods of visual image processing (filtering, highlighting contours, etc.). In this regard, one more requirement is put forward to encryption methods in the case of their application concerning images – this is the complete noise of the encrypted image. This is necessary so that the use of visual image processing methods becomes impossible. The RSA algorithm is one of the most widely known industrial standards for encrypting signals. Unlike symmetric encryption, in an open-key encryption scheme, it is impossible to calculate the decryption procedure, knowing the encryption procedure. Namely, the working time of the algorithm for calculating the decryption procedure is so great that it cannot be implemented on any modern computers, as well as on computers of the future. Such coding schemes are called asymmetric. Therefore, the urgent task is to implement the application of the RSA algorithm so that when encrypting an image: – the cryptographic stability of the RSA algorithm has not become worse; – the full image noise was achieved to prevent the use of visual image processing techniques. The algorithm of elements of the RSA algorithm, as the most resistant to unauthorized decryption of signals, and bitwise operations for a compatible combination during encryption and decryption of images is proposed by the authors. Encryption – decryption is performed without additional noise. The proposed algorithm is applied to images in which there are strictly extracted contours. Elements of the RSA algorithm are assigned to perform bitwise operations on the intensity values of pixels of a color image. The developed algorithm has higher cryptographic stability compared to the traditional RSA algorithm. The authors described the possibilities of using elements of the RSA algorithm in bitwise transformations when encrypting and decrypting images. The results of encryption simulation for cryptographic transformations of color images of a given dimension are presented. Modified models and algorithmic procedures of key formation processes of direct and inverse cryptographic transformations have been developed. They are reduced to elemental mathematical operations.
dc.format.extent5-10
dc.format.pages6
dc.identifier.citationKovalchuk A. Bit operations with elements of the RSA algorithm in encryption-decryption of color images / Anatoliy Kovalchuk, Yuriy Peleckh, Tetiana Bubela // Measuring equipment and metrology. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 83. — No 3. — P. 5–10.
dc.identifier.citationenKovalchuk A. Bit operations with elements of the RSA algorithm in encryption-decryption of color images / Anatoliy Kovalchuk, Yuriy Peleckh, Tetiana Bubela // Measuring equipment and metrology. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 83. — No 3. — P. 5–10.
dc.identifier.doidoi.org/10.23939/istcmtm2022.03.005
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/59066
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofВимірювальна техніка та метрологія, 3 (83), 2022
dc.relation.ispartofMeasuring equipment and metrology, 3 (83), 2022
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dc.relation.referencesen[1] Michael Vollmer, Klaus-Peter Mollmann, Fundamentals of Infrared Thermal Imaging. Infrared Thermal Imaging, 10.1002 9783527693306, 2017. https://www.wiley.com/enus/Infrared+Thermal+Imaging:+Fundamentals,+Research+and+Applications,+2nd+Edition-p-9783527413515.
dc.relation.referencesen[2] B. Usmonov, O. Evsutin, A. Iskhakov, A. Shelupanov, A. Iskhakova, R. Meshcheryakov, "The cybersecurity in development of IoT embedded technologies", in Proc. International Conference on Information Science and Communications Technologies (ICISCT) IEEE, 2017, pp. 1–4. DOI: 10.1109/ICISCT.2017.8188589.
dc.relation.referencesen[3] D. Wagh, H. Fadewar, & G. Shinde, "Biometric Finger Vein Recognition Methods for Authentication", Computing in Engineering and Technology, pp. 45–53, 2020. DOI: 10.1007/978-981-32-9515-5-5.
dc.relation.referencesen[4] P. Chanukya, T. Thivakaran, "Multimodal biometric cryptosystem for human authentication using fingerprint and ear", Multimedia Tools and Applications, 79(1–2), pp. 659–673, 2020. DOI: 10.1007/s11042-019-08123-w.
dc.relation.referencesen[5] L.Valechha, H. Valecha, V. Ahuja, T. Chawla, & S. Sengupta, "Orisyncrasy – An Ear Biometrics on the Fly Using Gabor Filter", In Advances in Data Sciences, Security and Applications, pp. 457–466, 2020. DOI: 10.1007/978-981-15-0372-6-37.
dc.relation.referencesen[6] J. Yang, L. Liu, T. Jiang, Y. Fan, "A modified Gabor filter design method for fingerprint image enhancement", Pattern Recognition Letters, 24(12), pp. 1805–1817, 2003. DOI: 10.1016/S0167-8655(03)00005-9.
dc.relation.referencesen[7] Majid Rabbani, Rajan Joshi. "An overview of the JPEG2000 still image compression standard", Eastman Kodak Company, Rochester, NY 14650, USA, Signal Processing: Image Communication, no. 17, vol. 1, pp. 3–48, 2002. https://scirp.org/reference/referencespapers.aspx?referenceid=727652.
dc.relation.referencesen[8] A. Kovalchuk, I. Izonin, C. Strauss, M. Podavalkina, N. Lotoshynska, N. Kustra. "Image encryption and decryption schemes using linear and quadratic fractal algorithms and their systems", CEUR Workshop Proceedings, vol. 2533, 2019, pp. 139–150. https://doi.org/10.23939/istcmtm2020.04.025.
dc.relation.referencesen[9] A. Kovalchuk, I. Izonin, Gregush Ml, M., N. Lotoshyiiska, "An approach towards image encryption and decryption using quaternary fractional-linear operations", Procedia Computer Science, vol. 160, 2019, pp. 491–496. Conference Paper (Open Access), DOI : 10.1016 /j.procs. 2019.11.059
dc.relation.referencesen[10] S. X. Liao and M. Pawlak, "On image analysis by moments", IEEE Transaction on Pattern Analysis and Machine Intelligence, 18, no. 3, pp. 254–266. https://ieeexplore.ieee.org/document/485554.
dc.relation.referencesen[11] E. M. Haacke, R.W. Brown, M.R. Thompson and R. Venkatesan, Magnetic Resonance Imagin: Physical Principles and Sequence Design. John Wiley & Sons, New York,1999. https://www.wiley.com/ensg/Magnetic+ Resonance+ Imaging:+Physical+Principles+and+Sequence+Design,+2nd+Edition-p-9780471720850.
dc.relation.referencesen[12] J. T. Kajiya, The rendering equation. Computer Graphics, vol. 20, is. 4, pp. 143–150, 1986. https://dl.acm.org/ doi/10.1145/15886.15902.
dc.relation.referencesen[13] M. Sarfraz. Introductory Chapter: On Digital Image Processing, 2020. DOI: 10.5772 intechopen.92060, https://www.intechopen.com/chapters/71817.
dc.relation.referencesen[14] Ehsan Samei, Donald J Peck, Projection X-ray Imaging, Hendee’s Physics of Medical Imaging, 10.10029781118671016, pp. 217–242, 2019. https://onlinelibrary.wiley.com/doi/10.1002/9781118671016.ch6.
dc.relation.referencesen[15] B. Schneier. Applied Cryptography: Protocols, Algorithms and Source Code in C, Triumf, 2003. https://www.amazon.com/Applied-Cryptography-Protocols-Algorithms-Source/dp.
dc.relation.referencesen[16] [B. Jane. Digital Image Processing. Springer–Verlag Berlin Heidelberg, 2005. https://www.amazon.com/Digital-Image-Processing-Algorithms-Applications/dp/3540592989.
dc.relation.referencesen[17] R. C. Gonzales and R.E. Woods, Digital image processing, Prentice Hall, Upper Saddle River. 2002. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/ http://sdeuoc.ac.in/sites/default/files/sde_videos/Digital%20Image%20Processing%203rd%20ed.%20-%20R.%20Gonzalez%2C%20R.%20Woods-ilovepdfcompressed.pdf.
dc.relation.referencesen[18] I. Tsmots, O. Riznyk, V. Rabyk, Y. Kynash, N. Kustra, M. Logoid, Implementation of FPGA-Based Barker’s- Like Codes. In: Lytvynenko V., Babichev S., Wójcik W., Vynokurova O., Vyshemyrskaya S., Radetskaya S. (eds) "Lecture Notes in Computational Intelligence and Decision Making", ISDMCI 2019, Advances in Intelligent Systems and Computing, vol. 1020. Springer, Cham, 2020. DOI: 10.1007/978-3-030-26474-1_15.
dc.relation.referencesen[19] Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing", published by Pearson Education, Inc, Publishing as Prentice Hall. 2002. http://sdeuoc.ac.in/sites/default/files/sde_videos/Digital%20Image%20Processing%203rd%20ed.%20-%20R.%20Gonzalez%2C%20R.%20Woods-lovepdfcompressed.pdf.
dc.relation.referencesen[20] B. Girod, "The information theoretical significance of spatial and temporal masking in video signals", Proc. of the SPIE Symposium on Electronic Imaging, vol. 1077, 1989, pp. 178–187. https://typeset.io/papers/the-information-theoretical-significance-of-spatial-and-2bas6i0mgw.
dc.relation.urihttps://www.wiley.com/enus/Infrared+Thermal+Imaging:+Fundamentals,+Research+and+Applications,+2nd+Edition-p-9783527413515
dc.relation.urihttps://scirp.org/reference/referencespapers.aspx?referenceid=727652
dc.relation.urihttps://doi.org/10.23939/istcmtm2020.04.025
dc.relation.urihttps://ieeexplore.ieee.org/document/485554
dc.relation.urihttps://www.wiley.com/ensg/Magnetic+
dc.relation.urihttps://dl.acm.org/
dc.relation.urihttps://www.intechopen.com/chapters/71817
dc.relation.urihttps://onlinelibrary.wiley.com/doi/10.1002/9781118671016.ch6
dc.relation.urihttps://www.amazon.com/Applied-Cryptography-Protocols-Algorithms-Source/dp
dc.relation.urihttps://www.amazon.com/Digital-Image-Processing-Algorithms-Applications/dp/3540592989
dc.relation.urihttp://sdeuoc.ac.in/sites/default/files/sde_videos/Digital%20Image%20Processing%203rd%20ed.%20-%20R.%20Gonzalez%2C%20R.%20Woods-ilovepdfcompressed.pdf
dc.relation.urihttp://sdeuoc.ac.in/sites/default/files/sde_videos/Digital%20Image%20Processing%203rd%20ed.%20-%20R.%20Gonzalez%2C%20R.%20Woods-lovepdfcompressed.pdf
dc.relation.urihttps://typeset.io/papers/the-information-theoretical-significance-of-spatial-and-2bas6i0mgw
dc.rights.holder© Національний університет “Львівська політехніка”, 2022
dc.subjectEncryption
dc.subjectColor image
dc.subjectBitwise operations
dc.subjectContour
dc.subjectPixel intensity
dc.subjectDecryption
dc.subjectMatrix of pixel intensities
dc.titleBit operations with elements of the RSA algorithm in encryption-decryption of color images
dc.typeArticle

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