Maintaining a resilient computer network is a delicate task with conflicting priorities. Flows should be served while controlling risk due to attackers. Upon publication of a vulnerability, administrators scramble to manually mitigate risk while waiting for a patch. We introduce FASHION: a linear optimizer that balances routing flows with the security risk posed by these flows. FASHION formalizes routing as a multi-commodity flow problem with side constraints. FASHION formulates security using two approximations of risk in a probabilistic attack graph (Frigault et al., Network Security Metrics 2017). FASHION's output is a set of software-defined networking rules consumable by Frenetic (Foster et al., ICFP 2011). We introduce a topology generation tool that creates data center network instances including flows and vulnerabilities. FASHION is executed on instances of up to 600 devices, thousands of flows, and million edge attack graphs. Solve time averages 30 minutes on the largest instances (seconds on the smallest instances). To ensure the security objective is accurate, the output solution is assessed using risk as defined by Frigault et al. FASHION allows enterprises to reconfigure their network in response to changes in functionality or security requirements.
翻译:维护具有复原力的计算机网络是一个复杂的任务, 具有相互冲突的优先事项。 在控制袭击者应承担的风险时, 流动应该用于控制袭击者的风险 。 在公布一个弱点时, 管理员在等待补丁时会拼凑手动减轻风险 。 我们引入 FASISION: 一个线性优化器, 平衡路线流动与这些流动所构成的安全风险 。 FASISION 将路径正规化为多通性流动问题, 附带限制 。 FASISISION 在概率攻击图表( Frigault et al., 网络安全气象2017)中使用两种风险近似值来设定安全性 。 FASISION 的输出是一套由Frenetic( Foster et al., ICFCFP (2011) 所理解的软件定义的网络规则。 我们引入一个顶层生成工具, 创建数据中心网络实例, 包括流动和脆弱性 。 FASISION 可以在多达600个装置、 流量和百万个边缘攻击图的情况下执行。 在最大情况下( 秒为最小的例子) 平均30分钟。 。 确保安全目标是准确的,, 利用Frigaustrault 和功能网络中定义的风险来评估产出解决方案。