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Automatic detection of security vulnerabilities in source code .

机译:自动检测源代码中的安全漏洞。

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摘要

Growing security requirements for systems and applications have raised the stakes on software security verification techniques. Static analysis has been widely used to detect vulnerabilities at compile time. It takes advantage of the relevant information generated by the compiler and scales well to large code base. However, it is limited to check low-level security properties that syntactically match concrete program actions. Recently, model-checking is settling and showing great promise in the arena of software verification. Nevertheless, it suffers from abstraction issues for deriving a model of the program that can be model-checked. In this thesis, we present our security verification approach that brings into a synergy static analysis and model-checking. This synergy leverages the advantages of both techniques. We use the static analysis to automatically generate a concise abstraction of the program. On the other-hand, the model-checking provides the capability and flexibility of specifying and verifying a wide range of properties, and we also benefit from the exhaustive program analysis provided by model-checking.
机译:对系统和应用程序日益增长的安全性要求增加了软件安全性验证技术的风险。静态分析已广泛用于在编译时检测漏洞。它利用了编译器生成的相关信息,并可以很好地扩展到大型代码库。但是,只能检查语法上与具体程序动作匹配的低级安全属性。最近,模型检查正在建立并在软件验证领域显示出巨大的希望。但是,它在派生可以进行模型检查的程序模型时遇到了抽象问题。在本文中,我们提出了一种安全验证方法,该方法将协同静态分析和模型检查结合在一起。这种协同作用充分利用了这两种技术的优势。我们使用静态分析来自动生成程序的简洁抽象。另一方面,模型检查提供了指定和验证各种属性的能力和灵活性,并且我们还受益于模型检查提供的详尽的程序分析。

著录项

  • 作者

    Yang, Xiao Chun.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Engineering Computer.;Information Technology.
  • 学位 M.A.Sc.
  • 年度 2009
  • 页码 126 p.
  • 总页数 126
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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