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Analysis, detection, and modeling of attacks in computer communication networks.

机译：分析，检测和建模计算机通信网络中的攻击。

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摘要

This dissertation begins with the description and analysis of a certain class of denial of service attacks along with an overview of techniques and tools used to discover and analyze them. Two new solutions to the problem of detecting this type of attack are introduced, developed, and evaluated. We demonstrate that one of these techniques can detect an average of 84% of the attacks and the other detects an average of 96%, all with no occurrence of a false alarm. (In this arena the latter may be more important than the former.) Having experienced first-hand the difficulty of creating a controlled environment for testing new attack detection techniques, we then describe the problems in this area and develop a new tool to be used in modeling and generating attacks.; The first detection technique is based on an in-depth analysis of an invariant traffic characteristic that appears to be affected by certain types of network attack. The main benefits of detecting attacks by monitoring traffic invariants are that (1) no prior knowledge of the attack's behavior is needed and (2) no template of ‘normal’ traffic activity is needed.; The second technique is based on detecting abnormalities in a measurable traffic characteristic and although a traffic template is required, it does not require prior knowledge of the behavior of attacks, an advantage over some types of anomaly-based detectors.
机译：本文从对特定类型的拒绝服务攻击的描述和分析开始，并概述了用于发现和分析它们的技术和工具。引入，开发和评估了两种用于检测此类攻击的新解决方案。我们证明，这些技术中的一种可以检测到平均84％的攻击，另一种可以检测到平均96％的攻击，所有这些都不会发生错误警报。 （在这个领域中，后者可能比前者更重要。）亲身经历了创建用于测试新攻击检测技术的受控环境的困难之后，我们将描述该领域中的问题并开发新的工具来使用在建模和生成攻击中。第一种检测技术基于对似乎受到某些类型的网络攻击影响的不变流量特征的深入分析。通过监视流量不变性来检测攻击的主要好处是：（1）无需事先了解攻击行为，并且（2）不需要“正常”流量活动的模板。第二种技术基于检测可测量的流量特征中的异常，并且尽管需要流量模板，但它不需要先验攻击行为，这是某些类型的基于异常的检测器的优势。

著录项

  • 作者

    Allen, William H.;

  • 作者单位

    University of Central Florida.;

  • 授予单位 University of Central Florida.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 223 p.
  • 总页数 223
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

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