MapReduce在云计算系统中的计算完整性机制

A. Bendahmane, M. Essaaidi, A. El Moussaoui, A. Younes
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引用次数: 0

摘要

MapReduce作为一种强大的并行数据处理模型被广泛使用,被大多数云提供商采用来构建云计算框架。然而,在开放云系统中,计算的安全性成为一个巨大的挑战。此外,MapReduce数据处理服务是长时间运行的,这增加了攻击者对worker发起攻击的可能性,并使它们恶意行为,然后篡改用户任务的计算完整性,其中它们的执行通常在用户控制之外的不同管理域中执行。因此,计算结果可能是错误的和不诚实的。本文提出了一种新的基于加权t优先投票的机制来保证MapReduce在开放云计算环境下的完整性。我们的机制可以同时击败合谋和非合谋的恶意实体,从而保证了较高的计算精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computaion integrity mechanism for MapReduce in cloud computing system
MapReduce has been widely used as a powerful parallel data processing model and is adopted by most cloud providers to build cloud computing framework. However, in open cloud systems, security of computation becomes a great challenge. Moreover, MapReduce data-processing services are long-running, which increases the possibility that an adversary launches an attack on the workers and make them behave maliciously and then tamper with the computation integrity of user tasks where their executions are generally performed in different administration domains out of the user control. Thus, the results of the computation might be erroneous and dishonest. In this paper, we propose a new mechanism based on weighted t-first voting method for ensuring the integrity of MapReduce in open cloud computing environment. Our mechanism can defeat both collusive and non-collusive malicious entities and therefore guarantee high computation accuracy.
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