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首页> 外文期刊>International journal of modeling, simulation and scientific computing >A secure data protection technique for healthcare data in the cloud using homomorphic encryption and Jaya—Whale optimization algorithm
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A secure data protection technique for healthcare data in the cloud using homomorphic encryption and Jaya—Whale optimization algorithm

机译:使用同态加密和Jaya-Whale优化算法的云中医疗数据的安全数据保护技术

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摘要

Cloud computing has become a powerful mechanism for initiating secure communication among users. The advancements in the technology lead to provide various services, like accessing network, resources, and platform. However, handling large datasets and security are major issues in the cloud systems. Hence, this paper proposes a technique, namely, Jaya-Whale Optimization (JWO), which is the integration of Jaya algorithm and Whale optimization algorithm (WOA) and adapts homomorphic encryption for initiating secure data transmission in the cloud. The original data are preserved by generating Data Protection (DP) coefficient using the proposed JWO algorithm. In the proposed algorithm, the fitness is calculated based on privacy and utility parameters for selecting the optimal solution. Also, the sanitized data are generated by EXORing the Key Information Product (KIP) matrix and key vector. Finally, the data owner provides the key to the users for retrieving the original data from the sanitized data. The experimentation is carried out using Cleveland, Hungarian, and Switzerland datasets in terms of BD, accuracy, and fitness and the analysis shows that the proposed JWO provides superior performance in terms of BD, accuracy, and fitness parameters with values 0.720, 0.822, and 0.722.
机译:云计算已成为在用户之间发起安全通信的强大机制。技术的进步导致提供各种服务,例如访问网络,资源和平台。但是,处理大型数据集和安全性是云系统中的主要问题。因此,本文提出了一种技术,即Jaya-Whale优化(JWO),它是Jaya算法和Whale优化算法(WOA)的集成,并采用同态加密来启动云中的安全数据传输。通过使用提出的JWO算法生成数据保护(DP)系数,可以保留原始数据。在提出的算法中,基于隐私和效用参数计算适应度,以选择最佳解决方案。同样,通过对密钥信息积(KIP)矩阵和密钥向量进行异或运算,生成清理后的数据。最后,数据所有者向用户提供密钥,以便从经过清理的数据中检索原始数据。使用克利夫兰,匈牙利和瑞士的数据集进行了BD,准确性和适用性方面的实验,分析表明,所提出的JWO在BD,准确性和适用性参数方面具有出色的性能,其值分别为0.720、0.822和0.722。

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