Abstract
In medical imaging, image security is crucial yet difficult to implement. To protect medical images, numerous studies have been carried out. Image confidentiality may be achieved using encryption without the risk of data loss. Traditional encryption approaches cannot be used to protect e-health data directly because of restrictions on data size, redundancy, and capability, particularly when medical data are transported via unencrypted networks. Because images differ from text, they have a greater potential for loss of information and privacy; patients may no longer be able to access their data. Researchers have recognized these security risks and have suggested several image encryption approaches to address the issue. However, the researchers discovered that the proposed solutions still have several application-specific security issues. To provide an effective image encryption method for the healthcare sector, this study offers a novel cuttlefish particle swarm-optimized ciphertext-policy weighted attribute (CPSOCPWA) algorithm. The security and computation time of the suggested method is examined, assessed, and then contrasted with those of typically encrypted methods. It has been determined how well the proposed method performs using a large number of test images. Numerous tests demonstrate that the suggested approach performs better than traditional methods.
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Senthilkumar, M. et al. (2024). A Novel Encryption Framework to Improve the Security of Medical Images. In: Devi, B.R., Kumar, K., Raju, M., Raju, K.S., Sellathurai, M. (eds) Proceedings of Fifth International Conference on Computer and Communication Technologies. IC3T 2023. Lecture Notes in Networks and Systems, vol 897. Springer, Singapore. https://doi.org/10.1007/978-981-99-9704-6_13
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DOI: https://doi.org/10.1007/978-981-99-9704-6_13
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