Evolutionary based moving target cyber defense
Evolutionary based moving target cyber defense
复制标题
基于进化的移动目标网络防御
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Errin W. Fulp
中科院分区：
文献类型：
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作者：
D. J. John;Robert W. Smith;William H. Turkett;Daniel A. Cañas;Errin W. Fulp
移动目标（MT）防御不断改变系统的攻击面，试图限制攻击者收集的侦察的有用性。这种防御策略的一种方法是间歇性地改变系统的配置。这些变化必须保持功能性和安全性，同时也是多样化的。找到合适的配置变化，形成MT防御是具有挑战性的。在没有充分理解设置的相互依赖性的情况下，可能需要考虑大量的单个配置设置。基于进化的算法，从好的解决方案中制定更好的解决方案，可以用来创建MT防御。新的配置是基于先前配置的安全性创建的，并且可以定期实施以改变系统的攻击面。这种方法不仅能够发现新的、更安全的配置，而且还具有主动性和弹性，因为它可以以类似于自然界中发现的系统的方式不断适应当前环境。本文介绍并比较了两种遗传算法来创建MT防御。两者之间的主要区别是基于他们的突变方法。一个变量改变值，另一个变量修改从中选择值的域。
A Moving Target (MT) defense constantly changes a system's attack surface, in an attempt to limit the usefulness of the reconnaissance the attacker has collected. One approach to this defense strategy is to intermittently change a system's configuration. These changes must maintain functionality and security, while also being diverse. Finding suitable configuration changes that form a MT defense is challenging. There are potentially a large number of individual configurations' settings to consider, without a full understanding of the settings' interdependencies. Evolution-based algorithms, which formulate better solutions from good solutions, can be used to create a MT defense. New configurations are created based on the security of previous configurations and can be periodically implemented to change the system's attack surface. This approach not only has the ability to discover new, more secure configurations, but is also proactive and resilient since it can continually adapt to the current environment in a fashion similar to systems found in nature. This article presents and compares two genetic algorithms to create a MT defense. The primary difference between the two is based on their approaches to mutation. One mutates values, and the other modifies the domains from which values are chosen.