POSTER: RIA: an Audition-based Method to Protect the Runtime Integrity of MapReduce Applications

Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security Pub Date : 2016-10-24 DOI:10.1145/2976749.2989042

Yongzhi Wang, Yulong Shen

引用次数: 2

Abstract

Public cloud vendors have been offering varies big data computing services. However, runtime integrity is one of the major concerns that hinders the adoption of those services. In this paper, we focus on MapReduce, a popular big data computing framework, propose the runtime integrity audition (RIA), a solution to verify the runtime integrity of MapReduce applications. Based on the idea of RIA, we developed a prototype system, called MR Auditor, and tested its applicability and the performance with multiple Hadoop applications. Our experimental results showed that MR Auditor is an efficient tool to detect runtime integrity violation and incurs a moderate performance overhead.

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海报:RIA:一个基于审核的方法来保护MapReduce应用程序的运行时完整性

公共云供应商一直在提供各种大数据计算服务。然而，运行时完整性是阻碍采用这些服务的主要问题之一。本文以流行的大数据计算框架MapReduce为研究对象，提出了一种验证MapReduce应用运行时完整性的解决方案——运行时完整性测试(RIA)。基于RIA的思想，我们开发了一个名为MR Auditor的原型系统，并在多个Hadoop应用中测试了它的适用性和性能。实验结果表明，MR Auditor是一种有效的检测运行时完整性违规的工具，并且产生适度的性能开销。

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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Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security

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