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Malware Vectors: A Technique for Discovering Defense Logics.

机译:恶意软件媒介:一种发现防御逻辑的技术。

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摘要

Organizations face Cyber attacks of increasing sophistication. However, detection measures have not kept up with the pace of advancement in attack design. Common detection systems use detection rules or heuristics based on behaviors of known previous attacks and often crafted manually. The result is a defensive system which is both too sensitive, result- ing in many false positives, and not sensitive enough, missing detection of new attacks.;Building upon our work developing the Covertness Capability Calculus, we propose Malware Vectors, a technique for the discovery of defense logic via remote probing. Malware Vectors proposes a technique for building malware by discovering obserables which can be generated without triggering detection. Malware Vectors generates probes to establish a vector of acceptable observable values that the attack may generate without triggering detection. We test attacks against an unknown defense logic and show that it is trivial to discover a covert way to carry out an attack. We extend this simulation to randomly generated defense logics and find that without a change in underlying strategy defenders cannot improve their position significantly. Further, we find that discovery of full logic can be efficiently achieved using only Membership Queries in most cases. Finally, we propose some techniques that a defender could implement to attempt to defend against the Malware Vectors technique.
机译:组织面临日益复杂的网络攻击。但是,检测措施未能跟上攻击设计的发展步伐。常见的检测系统基于已知的先前攻击的行为使用检测规则或启发式方法,并且通常是人工制作的。结果是防御系统既过于敏感,导致许多误报,又不够敏感,缺少对新攻击的检测。;基于我们开发隐蔽能力演算的工作,我们提出了恶意软件矢量,一种用于通过远程探测发现防御逻辑。恶意软件媒介提出了一种通过发现可观察到的,无需触发检测即可生成的可观察对象来构建恶意软件的技术。恶意软件向量会生成探针,以建立可接受的可观察值的向量,攻击可能会在不触发检测的情况下生成这些向量。我们针对未知的防御逻辑对攻击进行了测试,并表明发现秘密进行攻击的方法是微不足道的。我们将此模拟扩展到随机生成的防御逻辑,发现如果不改变基础策略,防御者就无法显着提高其地位。此外,我们发现在大多数情况下,仅使用成员资格查询就可以有效地实现完整逻辑的发现。最后,我们提出防御者可以实施的一些技术,以尝试防御恶意软件向量技术。

著录项

  • 作者

    Stocco, Gabriel Fortunato.;

  • 作者单位

    Dartmouth College.;

  • 授予单位 Dartmouth College.;
  • 学科 Computer engineering.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 121 p.
  • 总页数 121
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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