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Abstract semantics for software security analysis.

机译:软件安全性分析的抽象语义。

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摘要

Program analysis and formal methods have enabled advanced automatic software security analysis such as security policy enforcement and vulnerability discovery. However, due to the complexity of the modern software, recent applications of such techniques exhibit serious usability and scalability problems. In this thesis, we address these problems using automatically or semi-automatically constructed abstract program semantics. Specifically, we study two typical scenarios where the power of formal techniques is limited by the problems above, and develop novel techniques that address these issues. First, we propose a new algorithm to construct event-based program abstraction, and check contextual security policies under this abstraction. Our approach addresses the usability and scalability problems in the model-checking of security policies in event-driven programs. Second, we propose a synthesis-based algorithm to learn and check web server logic without having access to the server-side source code. The key insight is that the client-side behavior reflects partially the server-side logic, thus we infer server-side logic by observing the client-side's execution. We develop a declarative language to encode our domain specific modeling of common server-side operations, as well as an efficient algorithm to synthesize a server model in that language. In summary, we demonstrate that abstract semantics can bridge the gap between the human and the massive details of the program, and make formal techniques applicable in a large scale.
机译:程序分析和形式方法使高级自动软件安全分析成为可能,例如安全策略实施和漏洞发现。但是,由于现代软件的复杂性,这种技术的最新应用显示出严重的可用性和可伸缩性问题。在本文中,我们使用自动或半自动构造的抽象程序语义来解决这些问题。具体来说,我们研究了两种典型的情况,即形式技术的功能受到上述问题的限制,并开发了解决这些问题的新颖技术。首先,我们提出了一种新的算法来构造基于事件的程序抽象,并在此抽象下检查上下文安全策略。我们的方法解决了事件驱动程序中安全策略的模型检查中的可用性和可伸缩性问题。其次,我们提出了一种基于综合的算法来学习和检查Web服务器逻辑,而无需访问服务器端源代码。关键的见解是客户端行为部分反映了服务器端逻辑,因此我们通过观察客户端的执行来推断服务器端逻辑。我们开发了一种声明性语言来对常见服务器端操作的域特定模型进行编码,并开发了一种有效的算法来以该语言综合服务器模型。总而言之,我们证明了抽象语义可以弥合程序的人与人之间的鸿沟,并使正式技术可以大规模应用。

著录项

  • 作者

    Chen, Zhijie.;

  • 作者单位

    University of California, Berkeley.;

  • 授予单位 University of California, Berkeley.;
  • 学科 Computer science.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 87 p.
  • 总页数 87
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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