A moving target environment for computer configurations using Genetic Algorithms
A moving target environment for computer configurations using Genetic Algorithms
复制标题
使用遗传算法的计算机配置的移动目标环境
DOI：
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发表时间：
2011
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：
Michael B. Crouse;Errin W. Fulp
计算机系统的移动目标 (MT) 环境通过更改计算机配置中明确定义的各种系统属性，通过多样性提供安全性。时间分集可以通过周期性配置改变来实现；然而，在多台具有相似用途的计算机组成的基础设施中，多样性也必须是空间性的，以确保多台计算机不会同时共享相同的配置和潜在的漏洞。考虑到可能发生的变化的数量及其潜在的相互依赖性，发现安全、实用且多样化的计算机配置具有挑战性。本文描述了如何使用遗传算法 (GA) 来查找时间和空间上多样化的安全计算机配置。在所提出的方法中，计算机配置被建模为染色体，其中个体配置设置是性状或等位基因。遗传算法通过组合多个染色体（配置）来运行，这些染色体经过可行性测试并根据性能进行排名，性能将作为对攻击的抵抗力进行衡量。由于交叉和变异过程，遗传算法的连续迭代产生的配置通常更加安全和多样化。模拟结果将证明这种方法可以通过发现时间和空间上多样化的安全配置，在 MT 环境中为具有类似用途的计算机的大型基础设施提供服务。
Moving Target (MT) environments for computer systems provide security through diversity by changing various system properties that are explicitly defined in the computer configuration. Temporal diversity can be achieved by making periodic configuration changes; however in an infrastructure of multiple similarly purposed computers diversity must also be spatial, ensuring multiple computers do not simultaneously share the same configuration and potential vulnerabilities. Given the number of possible changes and their potential interdependencies discovering computer configurations that are secure, functional, and diverse is challenging. This paper describes how a Genetic Algorithm (GA) can be employed to find temporally and spatially diverse secure computer configurations. In the proposed approach a computer configuration is modeled as a chromosome, where an individual configuration setting is a trait or allele. The GA operates by combining multiple chromosomes (configurations) which are tested for feasibility and ranked based on performance which will be measured as resistance to attack. Successive iterations of the GA yield configurations that are often more secure and diverse due to the crossover and mutation processes. Simulations results will demonstrate this approach can provide at MT environment for a large infrastructure of similarly purposed computers by discovering temporally and spatially diverse secure configurations.