A Novel Optimal Key Selection Approach for Medical Image Encryption
A Novel Optimal Key Selection Approach for Medical Image Encryption |
||
![]() |
![]() |
|
© 2024 by IJETT Journal | ||
Volume-72 Issue-8 |
||
Year of Publication : 2024 | ||
Author : Afreen Fatima Mohammed, Syed Shabbeer Ahmad |
||
DOI : 10.14445/22315381/IJETT-V72I8P134 |
How to Cite?
Afreen Fatima Mohammed, Syed Shabbeer Ahmad,"A Novel Optimal Key Selection Approach for Medical Image Encryption," International Journal of Engineering Trends and Technology, vol. 72, no. 8, pp. 364-377, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I8P134
Abstract
The medical industry has been facing challenges in protecting the medical records of patients. To sustain privacy, it is important to secure medical images during their transmission. Therefore, a security mechanism must be implemented while transmitting medical images over the network. In order to handle security concerns, health organizations must implement efficient security strategies such as encryption techniques that would employ a better key generation and selection practice. In this study, chaotic maps are employed for the generation of keys. A novel approach is proposed to perform the optimal key selection process, which is vital in influencing the performance of an encryption algorithm. Thereby, in this paper, a novel Chaotic Bio-inspired Boosted Remora Optimization Algorithm is proposed for achieving a secure image transmission system based on an optimal key selection approach.
Keywords
Chaotic maps, Lightweight elliptic curve cryptography, Optimization algorithm, Secret share construction approach.
References
[1] Ali Adel Kanso, and Mohammad Ghebleh, “An Efficient Lossless Secret Sharing Scheme for Medical Images,” Journal of Visual Communication and Image Representation, vol. 56, pp. 245-255, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Hadi Givi, Mohammad Dehghani, and Štěpán Hubálovský, “Red Panda Optimization Algorithm: An Effective Bio-inspired Metaheuristic Algorithm for Solving Engineering Optimization Problems,” IEEE Access, vol. 11, pp. 57203-57227, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Mohammad Kamrul Hasan et al., “Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications,” IEEE Access, vol. 9, pp. 47731-47742, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Mustapha Benssalah, Yasser Rhaskali, and Mohamed Salah Azzaz, “Medical Images Encryption Based on Elliptic Curve Cryptography and Chaos Theory,” 2018 International Conference on Smart Communications in Network Technologies (SaCoNeT), El Oued, Algeria, pp. 222-226, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Fawad Masood et al., “A Lightweight Chaos-Based Medical Image Encryption Scheme Using Random Shuffling and XOR Operations,” Wireless Personal Communications, vol. 127, pp. 1405–1432, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Laith Abualigah et al., “Aquila Optimizer: A Novel Meta-Heuristic Optimization Algorithm,” Computers & Industrial Engineering, vol. 157, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Olaide Nathaniel Oyelade et al., “Ebola Optimization Search Algorithm: A New Nature-Inspired Metaheuristic Optimization Algorithm,” IEEE Access, vol. 10, pp. 16150-16177, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Jeffrey O. Agushaka, Absalom E. Ezugwu, and Laith Abualigah, “Gazelle Optimization Algorithm: A Novel Nature-Inspired Metaheuristic Optimizer,” Neural Computing and Applications, vol. 35, pp. 4099–4131, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Heming Jia, Xiaoxu Peng, and Chunbo Lang, “Remora Optimization Algorithm,” Expert Systems with Applications, vol. 185, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Ibrahim Al-Shourbaji et al., “An Efficient Parallel Reptile Search Algorithm and Snake Optimizer Approach for Feature Selection,” Mathematics, vol. 10, no. 13, pp. 1-20, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] V. Sangavi, and P. Thangavel, “An Exotic Multi-Dimensional Conceptualization for Medical Image Encryption Exerting Rossler System and Sine Map,” Journal of Information Security and Applications, vol. 55, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Jalaluddin Khan et., “Medical Image Encryption Into Smart Healthcare IOT System,” 2019 16th International Computer Conference on Wavelet Active Media Technology and Information Processing, Chengdu, China, pp. 378-382, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[13] K. Shankar, and P. Eswaran, “Sharing a Secret Image with Encapsulated Shares in Visual Cryptography,” Procedia Computer Science, vol. 70, pp. 462-468, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Srinivasan Nagaraj, G.S.V. Prasada Raju, and K. Koteswara Rao, “Image Encryption Using Elliptic Curve Cryptography and Matrix,” Procedia Computer Science, vol. 48, pp. 276-281, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Hui Lu et al., “A Chaotic Non-Dominated Sorting Genetic Algorithm for the Multi-Objective Automatic Test Task Scheduling Problem,” Applied Soft Computing, vol. 13, no. 5, pp. 2790-2802, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Ahmed A. Abd EL-Latif et al., “Controlled Alternate Quantum Walks Based Privacy Preserving Healthcare Images in Internet of Things,” Optics & Laser Technology, vol. 124, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Jalaluddin Khan et al., “SMSH: Secure Surveillance Mechanism on Smart Healthcare IoT System with Probabilistic Image Encryption,” IEEE Access, vol. 8, pp.15747-15767, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[18] M. Geetha, and K. Akila, “Survey: Cryptography Optimization Algorithms,” International Journal of Emerging Technology and Innovative Engineering, vol. 5, no. 1, pp. 1-6, 2019.
[Google Scholar] [Publisher Link]
[19] Mohamed Elhoseny et al., “Hybrid Optimization with Cryptography Encryption for Medical Image Security in Internet of Things,” Neural Computing and Applications, vol. 32, pp. 10979-10993, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Archana S. Nadhan, and I. Jeena Jacob, “Enhancing Healthcare Security in the Digital Era: Safeguarding Medical Images with Lightweight Cryptographic Techniques in IoT Healthcare Applications,” Biomedical Signal Processing and Control, vol. 88, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Sonali Rout, and Ramesh Kumar Mohapatra, “Secure Video Steganographic Model Using Framelet Transform and Elliptic Curve Cryptography,” Multimedia Tools and Applications, vol. 83, pp. 25191–25212, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[22] B.T. Geetha et al., “Pigeon Inspired Optimization with Encryption Based Secure Medical Image Management System,” Computational Intelligence and Neuroscience, vol. 2022, no. 1, pp. 1-13, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Ravikumar Ch et al., “A Comparative Analysis for Deep Learning-Based Approaches for Image Forgery Detection,” International Journal of Systematic Innovation, vol. 8, no. 1, pp. 1-10, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[24] G. Suryanarayana et al., IOT for Healthcare, Modern Approaches in IoT and Machine Learning for Cyber Security, Springer, Cham, pp. 201-218, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Navoneel Chakrabarty, Brain MRI Images for Brain Tumor Detection, Kaggle, 2019. [Online] Available: https://www.kaggle.com/datasets/navoneel/brain-mri-images-for-brain-tumor-detection?select=yes
[26] Joseph Paul Cohen, Covid-Chestxray-Dataset, Github, 2020. [Online]. Available: https://github.com/ieee8023/covid-chestxray-dataset/tree/master/images
[27] Guangyue Kou et al., “Latin-Square-Based Key Negotiation Protocol for a Group of UAVs,” Electronics, vol. 12, no. 14, pp. 1-19, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Sachin Dattatraya Shingade, and Rohini Prashant Mudhalwadkar, “Hybrid Extreme Learning Machine Based Bidirectional Long Short‐Term Memory for Crop Prediction,” Concurrency and Computation: Practice and Experience, vol. 35, no. 2, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[29] David W. Sims et al., “Lévy Flight and Brownian Search Patterns of a Free-Ranging Predator Reflect Different Prey Field Characteristics,” Journal of Animal Ecology, vol. 81, no. 2, pp. 432-442, 2012.
[CrossRef] [Google Scholar] [Publisher Link]