针对PHR等高度机密云数据的高效轻量级安全系统

Sandeepkumar E V, Kayalvizhi Jayavel
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引用次数: 0

摘要

云存储系统中的服务器可以保存非常大量的个人健康记录(PHR)数据或信息。云平台的存储服务器提供长时间的存档服务。第三方基本上是云存储效率的管理员。这就是我们启动云存储服务的原因。云计算最大的困难之一是它很容易受到黑客攻击。普通的加密方法被用来保护信息不被窥探。所有秘密信息的密码都保存在一个由不同符号组成的系统中。删除编码以类似于用于计算分布式设置中的通信所需的不等码字密码的方式进行。当消息符号存储在分散环境中的不同服务器上时,加密术语符号也独立计算并存储。出于这个原因,我们引入并包含了一个阈值代理重加密方案。完全同态加密是一种很有前途的方法,可以通过限制谁可以查看敏感的PHR数据来保护数据。在发送加密的PHR数据时,代理重新加密机制在将PHR数据发送到接收方或存储服务器之前再次对其进行重新加密。当安全访问控制具有最大性能时,分配完成。鉴于此,我们期待看到PHR数据隐藏架构在增强v增强算法(EBA)上开发的施密特-萨摩亚公钥加密(SSPKE)方法。此外,在这一举措中,我们采用了多方协议准入控制程序来操作和访问用户的PHR数据,而不会危及敏感的云PHR数据隐私。实验结果表明,在综合考虑总处理时间、服务器响应时间和PHR数据分解率等指标的情况下,PHR的应用具有良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effective and light weight security system for highly confidential cloud data such as PHR
The server in a cloud storage system can hold a very large amount of Personal health records (PHR) data or information. The cloud platform's storage servers provide archival services for a lengthy time frame. The third party basically functions as an administrator for the efficiency of cloud storage. This is why we're starting up our cloud storage service. One of the biggest difficulties with the cloud is that it is vulnerable to hacking. Ordinary methods of encryption are used to safeguard the information from prying eyes. All of the secret messages' code words are kept in a system of varying symbols. Deletion coding is carried out in a manner analogous to that which is used to calculate the unequal code word cyphers required for a communication in a distributed setting. When the message symbols are stored in different servers in a dispersed environment, the cryptographic term signs are also calculated independently and stored. For this reason, we introduce and include a threshold proxy re-encryption scheme. Fully Homomorphic Encryption is a promising approach to securing sensitive PHR data by limiting who can view it. When sending encrypted PHR data, the proxy re-encryption mechanism re-encrypts the PHR data again before sending it on to the recipient or storage server. Allocation is completed when secure access control has maximised performance. In light of this, we expect to see the Schmidt-Samoa Public Key Encryption (SSPKE) method developed on the Enhanced v Boosting Algorithm (EBA) by PHR data Hiding Architecture. Additionally, in this initiative, we employ a procedure of multi-party protocol admission control to operate and access the user's PHR data without jeopardising the sensitive cloud PHR data privacy. The results of the experiments show the beneficial effect when various metrics, such as total processing time, server response time, and PHR data decomposition rate, are taken into account for the application of PHR.
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