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Protecting software from attack and theft via program analysis .

机译:通过程序分析保护软件免受攻击和盗窃。

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摘要

Along with the rapid developing software industry and the advent of the Internet, attack and theft are becoming two serious threats to software and software community. Although some attack or theft detection approaches have been proposed, these approaches are limited to meet several highly desired requirements. For example, both attack and theft detection approaches should be resilient to code obfuscation techniques; attack detection approaches should detect new or unknown attacks; software theft detection approaches should be able to detect software component theft.;In this dissertation, several new program analysis techniques, which meet these key requirements, are proposed to detect attack and theft. First, a novel program analysis technique called code abstraction is proposed which is a generic method to separate code from data. Based on this technique, an attack detection system called SigFree is designed and implemented. SigFree is signature free, thus it can block new and unknown attacks. Detection effectiveness and performance are evaluated in experiments and the applicability of SigFree is discussed. Second, a static taint and initialization analyses based approach is presented. Compared with existing static analysis approaches developed for the same purpose, the new approach is the first one that can detect attack code obfuscated by self-modifying and indirect jump, and a more comprehensive static analysis solution in defending against advanced obfuscation including anti-signature, anti-static-analysis and anti-emulation code obfuscation. Finally, a system call dependence graph based software birthmark is proposed to identify software theft. A dynamic analysis tool which generates system call dependence graph at run-time is designed and built. We demonstrate the strength of the birthmarks against various evasion techniques, including those based on different compilers and compiler optimization levels as well as state-of-the-art obfuscation tools. Unlike the existing works that were evaluated through toy software, we evaluate our birthmarks on a set of large software.
机译:随着快速发展的软件产业和Internet的出现,攻击和盗窃已成为对软件和软件社区的两个严重威胁。尽管已经提出了一些攻击或盗窃检测方法,但是这些方法被限制为满足一些高度期望的要求。例如,攻击和盗窃检测方法都应该对代码混淆技术具有弹性。攻击检测方法应检测到新的或未知的攻击;软件盗窃检测方法应该能够检测软件组件盗窃。本文提出了几种新的满足这些关键要求的程序分析技术来检测攻击和盗窃。首先,提出了一种称为代码抽象的新颖程序分析技术,这是一种将代码与数据分离的通用方法。基于此技术,设计并实现了一种名为SigFree的攻击检测系统。 SigFree没有签名,因此可以阻止新的未知攻击。在实验中评估了检测效率和性能,并讨论了SigFree的适用性。其次,提出了一种基于静态污点和初始化分析的方法。与出于相同目的而开发的现有静态分析方法相比,该新方法是第一个可以检测到通过自修改和间接跳转而被混淆的攻击代码的方法,并且是一种更全面的静态分析解决方案,可防御包括反签名,防静电分析和防仿真代码混淆。最后,提出了一种基于系统调用依赖图的软件胎记来识别软件盗窃行为。设计并构建了一个动态分析工具,该工具在运行时生成系统调用依赖图。我们展示了针对各种规避技术的胎记的优势,包括基于不同编译器和编译器优化级别以及最先进的混淆工具的规避技术。与通过玩具软件评估的现有作品不同,我们在一套大型软件上评估胎记。

著录项

  • 作者

    Wang, Xinran.;

  • 作者单位

    The Pennsylvania State University.;

  • 授予单位 The Pennsylvania State University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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