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一种基于改进猎豹优化算法的 AES-DES 新型算法,用于云环境中安全的医疗数据传输。

A novel AES-DES with improved Cheetah optimisation algorithm for secured medical data transmission in cloud environment.

机构信息

Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India.

Department of CSE, Rajeev Gandhi Memorial College of Engineering and Technology, Nandyal, India.

出版信息

J Med Eng Technol. 2024 Apr;48(3):100-117. doi: 10.1080/03091902.2024.2392550. Epub 2024 Sep 16.

Abstract

In recent years, transmitting medical data has been a regular process. Although strong, safe, and dependable encryption techniques are necessary for medical data, cryptography is largely a computational process. The research presents a selective encryption approach for the transfer of sensitive data. This study proposes a novel technique for selecting the optimal keys to offer more security to medical data. Initially, the medical data is encrypted using the hybrid AES-DES technique. To make an efficient encryption method, the most optimal keys are selected utilising an improved Cheetah optimisation algorithm (ICO). Finally, the keys are optimised, and the input medical data is safely kept in the cloud system according to the established model. As a result, the proposed approach utilises the Python tool to evaluate the results. The simulation results show that the proposed method outperforms others in terms of encryption time 96 s, decryption time 92 s, memory usage (16), and latency (0.006).

摘要

近年来,传输医学数据已成为一项常规流程。虽然医疗数据需要强大、安全和可靠的加密技术,但密码学在很大程度上是一个计算过程。本研究提出了一种用于传输敏感数据的选择性加密方法。本研究提出了一种选择最优密钥的新技术,为医疗数据提供更高的安全性。首先,使用混合 AES-DES 技术对医疗数据进行加密。为了实现高效的加密方法,利用改进的猎豹优化算法(ICO)选择最优密钥。最后,根据建立的模型优化密钥,并将输入的医疗数据安全地存储在云系统中。因此,该方法使用 Python 工具来评估结果。仿真结果表明,所提出的方法在加密时间 96s、解密时间 92s、内存使用(16)和延迟(0.006)方面优于其他方法。

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