RETRACTED ARTICLE: Quantum-enhanced cybersecurity analysis and medical image encryption in cloud IoT networks

Medical images are more crucial than other images in the majority of applications, particularly in real-time applications like telemedicine, a high level of safety and security is necessary for medical image transmission via open access. Privacy as well as security of patient medical picture data ha...

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Bibliographic Details
Published in:Optical and quantum electronics 2024-02, Vol.56 (4), Article 674
Main Authors: Priyadarshini, A, Abirami, S P, Ahmed, Mohammed Altaf, Arunkumar, B
Format: Article
Language:English
Subjects:
Artificial intelligence
Characterization and Evaluation of Materials
Computer Communication Networks
Cybersecurity
Electrical Engineering
Encryption
Error analysis
Image enhancement
Image transmission
Lasers
Machine learning
Medical imaging
Medical research
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
Privacy
Real time
Root-mean-square errors
Signal to noise ratio
Technology assessment
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Summary:Medical images are more crucial than other images in the majority of applications, particularly in real-time applications like telemedicine, a high level of safety and security is necessary for medical image transmission via open access. Privacy as well as security of patient medical picture data have become a crucial concern in recent image privacy protection research due to the quick development of artificial intelligence (AI) technology. This study suggests a unique method for encrypting medical images that integrates hybrid deep learning with cloud IoT network cyber security analysis. Here, the medical picture has been encrypted utilising deep, extreme convolutional networks and a stream crypto cypher in quantum techniques. After that, a secure cloud IoT architecture was used to store this encrypted image. The peak signal-to-noise ratio (PSNR), root mean square error (RMSE), structural similarity index measure (SSIM), mean average precision (MAP), and encryption speed are used in the experimental study. Analyses and simulations that were undertaken experimentally were done to gauge how well the suggested method worked. the proposed technique attained PSNR 92%, RMSE 85%, SSIM 68%, MAP 52% and encryption speed 88%.
ISSN:1572-817X
0306-8919
1572-817X
DOI:10.1007/s11082-023-06018-7