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When the cloud meets big data: Security challenges and solutions.

机译：当云遇到大数据时：安全挑战和解决方案。

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摘要

Cloud computing has emerged as the mainstay of cost-effective, high-performance platforms for hosting personal and organizational information assets and computing tasks. This thriving computing paradigm, however, also comes with security perils. Recent years have seen a rising trend of security breaches in the cloud. In this dissertation, we will propose novel techniques to understand and solve some of the security and privacy challenges of cloud computing.;First we present the design and implementation of a new framework to support high-performance auto-scaling detection services for cloud. This framework has been fully integrated into the existing cloud orchestration mechanism, allowing an ordinary cloud user to request a detection service and specify its parameters conveniently, through the cloud-formation file she submits for deploying her application.;Then we report a suite of new techniques that achieve secure and scalable read mapping on hybrid clouds. Our approach leverages the special features of the read mapping task, which only cares about small edit distances, and of the Cloud, which is good at handling a large amount of simple computation. These features enable us to split the mapping computation according to the seed-and-extend strategy.;Finally we examine security issues of mobile push messaging, which is one of the most important and popular mobile-cloud services. We will present the design and implementation of an automatic analysis tool for identifying vulnerabilities in push messaging SDKs and mobile applications that leverage these SDKs. The study reveals the serious security challenges those mobile cloud services are facing and the urgent need for the efforts to ensure their security qualities.
机译：云计算已经成为托管个人和组织信息资产以及计算任务的具有成本效益的高性能平台的支柱。但是，这种蓬勃发展的计算范例还带来了安全隐患。近年来，云中的安全漏洞呈上升趋势。本文将提出一些新颖的技术来理解和解决云计算的一些安全性和隐私性挑战。首先，我们提出了一个新框架的设计和实现，以支持高性能的云自动扩展检测服务。该框架已完全集成到现有的云编排机制中，允许普通云用户通过她提交的用于部署应用程序的云形成文件来请求检测服务并方便地指定其参数。然后，我们报告了一套新的在混合云上实现安全且可扩展的读取映射的技术。我们的方法利用了仅考虑较小编辑距离的读取映射任务的特殊功能，以及善于处理大量简单计算的Cloud的特殊功能。这些功能使我们能够根据种子和扩展策略拆分映射计算。最后，我们研究了移动推送消息传递的安全性问题，这是最重要和最受欢迎的移动云服务之一。我们将介绍一种自动分析工具的设计和实现，该工具可用于识别推式消息传递SDK和利用这些SDK的移动应用程序中的漏洞。该研究表明，这些移动云服务面临着严峻的安全挑战，并且迫切需要努力确保其安全质量。

著录项

  • 作者

    Chen, Yangyi.;

  • 作者单位

    Indiana University.;

  • 授予单位 Indiana University.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 158 p.
  • 总页数 158
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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