大数据环境下使用椭圆曲线加密实现分布式证书颁发

O. Shareef, A. Sagheer
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引用次数: 0

摘要

在大数据环境中,为了确保机密文件的交换安全,防止未经授权的访问,提高安全性是必要的。由一组不受信任的各方在大规模分布式系统中共享数据可能导致非法修改和未经授权的访问。因此,需要一个安全、快速的身份验证服务来对连接到系统的用户进行身份验证。基于椭圆曲线密码学(ECC),设计并实现了一种分布式证书颁发机构(DCA)方案,可以有效地提高分布式环境下大数据的认证能力。身份验证的角色分布在组中包含的许多节点之间。每个组都有自己的撤销和签名列表,而不是每个节点,这样可以减少系统开销,避免在没有集中服务器的情况下验证节点时花费大量时间。该方案在一个大型社交网络数据集上得到了验证。根据安全准则对该方案进行了分析,并与以往方案进行了比较,以评价其性能。实验表明,该方案能够减少内存的消耗和时间的消耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing a Distributed Certificate Authority Using Elliptic Curve Cryptography for Big Data Environment
Improving security is necessary to secure the exchange of confidential documents and protection against unauthorized accesses in the big data environment. Sharing data across a large-scale distributed system by a group of non-trusted parties can lead to illegal modification and unauthorized access. Thus, a secure and fast authentication service to authenticate the user connecting to the system is imperative. Based on Elliptic Curve Cryptography (ECC), a Distributed Certificate Authority (DCA) scheme has been designed and implemented which can efficiently improve the authentication of big data in a distributed environment. The role of authentication is distributed amongst the many nodes included in groups. Each group has its own revocation and signature list instead of each node, and this way reduces system overhead and avoids consuming much time when verifying the nodes without a centralized server. The proposed scheme is demonstrated on a big dataset of social networks. The scheme has been analyzed on the basis of security criteria and compare it with previous schemes to evaluate its performance. The experiment shows that the proposed scheme is capable of consumes less memory and reduces time consumption.
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