Security evaluation of cryptosystems used in cloud networks

S. Sadkhan, F. Abdulraheem
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引用次数: 12

Abstract

Cloud networking is the next generation architecture of IT. Clouds are very complex architectures. They have a replicated thousands of times, and common functional units and can be reduced to simple primitives. many issues related to security were created by complexity of cloud networking as well as all aspects of Cloud networking. Data security is one of the most important issues. The Cloud usually has a one security architecture but has many customers with variety requests. There are new risks introduced by clouds, like multi-tenancy, virtualization and data outsourcing in additional to existing security risks related to Cloud service providers (CSPs) and cloud customers (CCs). information security and their conformity with cloud networking security challenges targeted by Several international and industrial standards. Since there is a continuous increase in the field of communication regarding advanced data, there is an increase in need for time and statistical overhead that is associated with the application of cryptographic. Parallelizing the computation of cryptographic algorithms on many-core computing platforms can be a promising approach to reduce the execution time and eventually the energy consumption of such algorithms. In this paper we will analyze and compare a some of cryptosystems security evaluation approaches worked in cloud networking environment and depended on variety parameters to explain these approaches and show how it work in the few last years with the great modifying in cloud and great data growing.
云网络中使用的密码系统的安全性评估
云网络是下一代IT架构。云是非常复杂的架构。它们具有数千次的复制,并且具有共同的功能单元,并且可以简化为简单的原语。许多与安全相关的问题是由云网络的复杂性以及云网络的所有方面造成的。数据安全是最重要的问题之一。云通常只有一个安全架构,但有许多客户,他们有各种各样的要求。除了与云服务提供商(csp)和云客户(cc)相关的现有安全风险之外,云还带来了新的风险,如多租户、虚拟化和数据外包。信息安全及其与多项国际和行业标准所针对的云网络安全挑战。由于与高级数据相关的通信领域不断增加,因此需要增加与加密应用相关的时间和统计开销。在多核计算平台上并行化加密算法的计算可能是一种很有前途的方法,可以减少此类算法的执行时间并最终减少能耗。在本文中,我们将分析和比较一些在云网络环境下工作的密码系统安全评估方法,并依赖于各种参数来解释这些方法,并展示它在过去几年随着云环境的巨大变化和大数据的增长是如何工作的。
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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