A survey of image encryption for healthcare applications.

IF 2.3 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Evolutionary Intelligence Pub Date : 2023-01-01 Epub Date: 2022-06-14 DOI:10.1007/s12065-021-00683-x
Priyanka, Amit Kumar Singh
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引用次数: 0

Abstract

Recently, medical image encryption has attracted many researchers because of security issues in the communication process. The recent COVID-19 has highlighted the fact that medical images are consistently created and disseminated online, leading to a need for protection from unauthorised utilisation. This paper intends to review the various medical image encryption approaches along with their merits and limitations. It includes a survey, a brief introduction, and the most utilised interesting applications of image encryption. Then, the contributions of reviewed approaches are summarised and compared regarding different technical perspectives. Lastly, we highlight the recent challenges along with several directions of potential research that could fill the gaps in these domains for researchers and developers.

Abstract Image

Abstract Image

医疗保健应用图像加密调查。
最近,由于通信过程中的安全问题,医学图像加密吸引了许多研究人员。最近的 COVID-19 强调了这样一个事实,即医学图像一直在网上创建和传播,因此需要防止未经授权的使用。本文旨在回顾各种医学图像加密方法及其优点和局限性。它包括一项调查、简要介绍和最常用的有趣的图像加密应用。然后,从不同的技术角度总结和比较了已审查方法的贡献。最后,我们强调了近期面临的挑战以及几个潜在的研究方向,这些方向可以填补研究人员和开发人员在这些领域的空白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Evolutionary Intelligence
Evolutionary Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
6.80
自引率
0.00%
发文量
108
期刊介绍: This Journal provides an international forum for the timely publication and dissemination of foundational and applied research in the domain of Evolutionary Intelligence. The spectrum of emerging fields in contemporary artificial intelligence, including Big Data, Deep Learning, Computational Neuroscience bridged with evolutionary computing and other population-based search methods constitute the flag of Evolutionary Intelligence Journal.Topics of interest for Evolutionary Intelligence refer to different aspects of evolutionary models of computation empowered with intelligence-based approaches, including but not limited to architectures, model optimization and tuning, machine learning algorithms, life inspired adaptive algorithms, swarm-oriented strategies, high performance computing, massive data processing, with applications to domains like computer vision, image processing, simulation, robotics, computational finance, media, internet of things, medicine, bioinformatics, smart cities, and similar. Surveys outlining the state of art in specific subfields and applications are welcome.
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