Volume 8 , Issue 1 , PP: 42-52, 2021 | Cite this article as | XML | Html | PDF | Full Length Article
Vandana Roy 1 *
Doi: https://doi.org/10.54216/JCIM.080105
The field of cryptography oversees the development of methods for transforming information between coherent and incoherent formats. Encryption and decryption techniques controlled by keys maintain the privacy of the substance and who can access it. Private key cryptography refers to methods of encryption and decryption that employ the same secret key. The alternative is public key cryptography, wherever the encryption and decryption keys are different. It is essential for the sanctuary of any crypto scheme that the confusion and diffusion properties be met. While the diffusion property rearranges the pixels in an image, the confusion property simply replaces the pixel values. In-depth discussion of a genetic-algorithm-based hybrid approach to secure and complex three-dimensional chaos-based image encryption (SCIE) has been presented. Here, we use mathematics edge, multipoint edges operator, and coupled transmutation operatives to accomplish permutation. In this method, a key stream is created using a 3D CSI (Compound Sine and ICMIC) map. Using a private key, hybrid operators are used to encrypt data. Several metrics were considered while evaluating the suggested algorithm's efficacy, including the UACI (Unified Average Change Intensity), correlation constant, NPCR (Net Pixel Change Rate). Experiments with the same have shown promising results in protecting real-time photos.
SCIE , Image Encryption , NPCR , ICMIC , Information Security
[1]. Chen, C, Liu, J, Wen, Y & Dong, Z 2015, ‘A hybrid genetic algorithm for privacy and cost aware scheduling of data intensive work flow in cloud’, Springer, International Conference on Algorithms and Architectures for Parallel Processing, vol. 25, no. 1, pp. 578-591.
[2]. Chen, TY, Hwang, MS & Jan, JK 2013, ‘A secure image authentication scheme for tamper detection and recovery’, Imaging Science Journal, vol. 60, no. 4, pp. 219-233.
[3]. Congyang Chen, Jianxun Liu, Yiping Wen & Dong Zhou 2015, ‘A Hybrid Genetic Algorithm for Privacy and Cost Aware Scheduling of Data Intensive Work flow in Cloud’, Springer, vol. 9528, no. 1, pp. 578-591.
[4]. Das, S, Mandal, SN & Ghoshal, N 2014, ‘Diffusion and encryption of digital image using genetic algorithm’, Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing Theory and Applications (FICTA), vol. 12, no. 2, pp. 729-736.
[5]. Devaraj, P & Kavitha, C 2016, ‘An image encryption scheme using dynamic S-boxes’, Springer Science+Business Media Dordrecht, vol. 86, no. 2, pp. 927 - 940.
[6]. Dhivya Ravichandran & Padmapriya Praveenkumar 2016, ‘Chaos Based Edge and Mutation for Securing DICOM Image’, Computers in Biology and Medicine, vol. 72, no. 1, pp. 170 - 184.
[7]. Gaurav Bhatnagar, QM & Jonathan Wu 2012, ‘Selective image encryption based on pixels of interest and singular value decomposition’, Digital Signal Processing, vol. 22, no. 4, pp. 648-663.
[8]. Guesmi, R, Farah, MAB, Kachouri, A & Samet, M 2016, ‘Hash keybased image encryption using edge operator and chaos’, Multimedia Tools and Applications, vol. 75, no. 2, pp. 4753 - 4769.
[9]. Guodong Ye 2010, ‘Image scrambling encryption algorithm of pixel bit based on chaos map’, Pattern Recognition Letter, vol. 31, no. 5, pp. 347-354.
[10]. Huang, X & Ye, G 2014, ‘An image encryption algorithm based on hyper-chaos and DNA sequence’, Multimedia Tools and Applications, vol. 72, no. 1, pp. 57–70.
[11]. Huijuan Li, Yurong Wang , Haitao Yan, Liben Li, Quize Li & Xiaoyan Zhao 2013, ‘Double-image encryption by using chaos-based local pixel scrambling technique and gyrator transform’, Optics and Lasers in Engineering, vol. 51, no. 12, pp. 1327-1331.
[12]. Majid Khan & Tariq Shah 2014, ‘A novel image encryption technique based on Henon chaotic map and S8 symmetric group’, Neural Computing & Applications, vol.70, no. 8, pp. 1717-1722.
[13]. Manish Kumar & Sunil Kumar 2016, ‘Intertwining Logistic Map and Cellular Automata Based Color Image Encryption Model’, International Conference on Computational Techniques in Information and Communication Technologies, vol. 10, pp. 58-67.
[14]. Mohammad Ali Bani Younes & Aman Jantan 2008, ‘Image Encryption Using Block-Based Transformation Algorithm’, IAENG International Journal of Computer Science, vol. 35, no.1, pp. 35 - 46.
[15]. Muhammad Rafiq Abuturab 2017, ‘Multiple color-image fusion and watermarking based on optical interference and wavelet transform’, Optics and Lasers in Engineering, vol. 89, no. 1, pp. 47-58.
[16]. Pareek, NK & Patidar, V 2016, ‘Medical image protection using genetic algorithm’, Soft Computing, vol. 20, no. 2, pp. 763–772.
[17]. Ramzi Guesmi, Mohamed Amine Ben Farah & Abdennaceur Kachouri 2015, ‘Hash key-based image encryption using edge operator and chaos’, Springer, vol. 75, no. 8, pp. 4753-4769.
[18]. Roy V., Shukla S. (2013) Image Denoising by Data Adaptive and Non-Data Adaptive Transform Domain Denoising Method Using EEG Signal. In: Kumar V., Bhatele M. (eds) Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE 2012). Lecture Notes in Bioengineering. Springer, India. https://doi.org/10.1007/978-81-322-0970-6_2.
[19]. Subhajit Das, Satyendra Nath Mandal & Nabin Ghoshal 2014, ‘Diffusion and Encryption of Digital Image Using Genetic Algorithm’, Advances in intelligent computing-Springer, vol. 327, no. 1, pp. 729-736.
[20]. Tang, Z 2016, ‘Multiple- image encryption with bit-plane decomposition and chaotic maps’, Optics and Lasers in Engineering, vol. 80, no. 2, pp. 1-11.
[21]. Tao Xiang, Jia Hu & Jianglin Sun 2015, ‘Outsourcing chaotic selective image encryption to the cloud with steganography’, Digital Signal Processing, vol. 43, no. 4, pp. 28-37.
[22]. Xiang, T, Qu, J, Yu, C & Fu, X 2012, ‘Degradative encryption: An efficient way to protect SPIHT compressed images’, Optics Communication, Elsevier, vol. 285, no. 24, pp. 4891-4900.
[23]. Xingyuan Wang & Hui-li Zhang 2015, ‘A novel image encryption algorithm based on genetic recombination and hyper-chaotic systems’, Springer, vol. 83, no. 2, pp. 333-346.
[24]. Xu, L & Li, Z 2016, ‘A novel bit level image encryption algorithm based on chaotic maps’, Optics and Lasers in Engineering, vol. 78, no.1, pp. 17-25.
[25]. Xuancai Zhao, Qiuzhen Lin , Jianyong Chen, Jianping Yu & Zhong Ming 2016, ‘Optimizing security and quality of service in a Real-time database system using Multi-objective genetic algorithm’, Elsevier , vol. 64, no. 1, pp. 11-23.
[26]. V. Roy and S. Shukla, "Mth Order FIR Filtering for EEG Denoising Using Adaptive Recursive Least Squares Algorithm," 2015 International Conference on Computational Intelligence and Communication Networks (CICN), 2015, pp. 401-404, doi: 10.1109/CICN.2015.85.
[27]. Yadav, AK, Mehta, R, Kumar, R & Vishwakarma, VP 2016, ‘Lagrangian twin support vector regression and genetic algorithm based robust grayscale image watermarking’, Multimedia Tools and Applications, vol. 75, no. 15, pp. 9371-9394.
[28]. Yanbin Li, Feng Zhang & Yuan 2015, ‘Asymmetric multiple-image encryption based on the cascaded fractional Fourier transform’ Optics and Lasers in Engineering, vol. 72, no. 1, pp. 18-25.
[29]. Ahmad, M.; Haleem, H.; Khan, P.M. A new chaotic substitution box design for block ciphers. In Proceedings of the 2014 International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, 20–21 February 2014; IEEE: Piscataway, NJ, USA, 2014; pp. 255–258.
