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Practical static analysis framework for inference of security-related program properties.

机译:实用的静态分析框架,用于推断与安全性相关的程序属性。

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摘要

For the software quality and security concerns, it is important to reason about security-related program securities. We present a static analysis framework for inference of security-related program properties. Within this framework we infer ownership, immutability and information flow for the protection of object access, data confidentiality and integrity. We propose runtime models that capture these properties. We design and implement ownership, immutability and information flow inference analyses for Java. These analyses reveal information about object access and information flow in the program, and may help uncover serious vulnerabilities.;To evaluate the framework, an empirical investigation is performed on a set of Java components, and a set of small-to-large Java programs. The results indicate that the analyses are practical and precise. Therefore, the analyses can be integrated in program comprehension tools that support effective reasoning about software security and software quality.;The usage of the inferences is illustrated by several applications of the framework. Ownership analysis is applied on reasoning about shared objects in open concurrent Java programs. Three structural patterns for object sharing are identified: the shared objects are categorized as central, owned or distributed. We argue that these patterns facilitate the understanding of concurrent programs. The experiments on several medium-to-large Java programs reveal the structure of sharing in real-world Java programs.;The usage of the static information flow analysis is illustrated with three applications. The first application of information flow analysis is security violation detection. We perform experiments on a set of Java web applications and the experiments show that the information flow analysis effectively detects security violations. The second application is type inference. Our experiments on the Java web applications show that our flow analysis successfully infers security types. The last application studies the effect of thread-shared variables on thread-local variables. Our experiments on a set of multi-thread programs show that most of the thread-local variables are affected by the thread-shared variables.
机译:出于软件质量和安全性考虑,重要的是要对与安全性相关的程序安全性进行推理。我们提供了一个静态分析框架,用于推断与安全性相关的程序属性。在此框架内,我们推断所有权,不变性和信息流以保护对象访问,数据机密性和完整性。我们提出了捕获这些属性的运行时模型。我们为Java设计和实现所有权,不变性和信息流推断分析。这些分析揭示了程序中有关对象访问和信息流的信息,并可能有助于发现严重的漏洞。为了评估框架,对一组Java组件和一组小型Java程序进行了实证研究。 。结果表明该分析是实用和准确的。因此,可以将这些分析集成到程序理解工具中,以支持有关软件安全性和软件质量的有效推理。;推理的用法由框架的多个应用程序说明。所有权分析适用于在打开的并发Java程序中关于共享对象的推理。确定了对象共享的三种结构模式:共享的对象分为中央对象,拥有对象或分布式对象。我们认为这些模式有助于理解并发程序。在几个中型到大型Java程序上进行的实验揭示了在现实世界中Java程序中的共享结构。静态信息流分析的用法通过三个应用程序进行了说明。信息流分析的第一个应用是安全违规检测。我们在一组Java Web应用程序上进行了实验,实验表明,信息流分析可以有效地检测到安全违规行为。第二个应用是类型推断。我们在Java Web应用程序上的实验表明,我们的流分析成功地推断出安全类型。最后一个应用程序研究了线程共享变量对线程局部变量的影响。我们在一组多线程程序上的实验表明,大多数线程局部变量都受到线程共享变量的影响。

著录项

  • 作者

    Liu, Yin.;

  • 作者单位

    Rensselaer Polytechnic Institute.;

  • 授予单位 Rensselaer Polytechnic Institute.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 130 p.
  • 总页数 130
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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