Biblio
Filters: Keyword is network neighborhood partitioning [Clear All Filters]
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2017. If You Can'T Measure It, You Can'T Improve It: Moving Target Defense Metrics. Proceedings of the 2017 Workshop on Moving Target Defense. :115–118.
We propose new metrics drawing inspiration from the optimization domain that can be used to characterize the effectiveness of moving target defenses better. Besides that, we propose a Network Neighborhood Partitioning algorithm that can help to measure the influence of MTDs more precisely. The techniques proposed here are generic and could be combined with existing metrics. The obtained results demonstrate how additional information about the effectiveness of defenses can be obtained as well as how network neighborhood partitioning helps to improve the granularity of metrics.
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2017. If You Can'T Measure It, You Can'T Improve It: Moving Target Defense Metrics. Proceedings of the 2017 Workshop on Moving Target Defense. :115–118.
We propose new metrics drawing inspiration from the optimization domain that can be used to characterize the effectiveness of moving target defenses better. Besides that, we propose a Network Neighborhood Partitioning algorithm that can help to measure the influence of MTDs more precisely. The techniques proposed here are generic and could be combined with existing metrics. The obtained results demonstrate how additional information about the effectiveness of defenses can be obtained as well as how network neighborhood partitioning helps to improve the granularity of metrics.