2020 MOR Journal

  2020 Vol. 25, #3 - Modeling Kill Chains Probabilistically

One of the most challenging problems in modern strike warfare is the ability to attack time-sensitive targets, namely, targets that are vulnerable only for a relatively short period of time. Kill chains involving steps to find, fix, track, target, and engage the target characterize this process. Comparing the kill chain timeline to the time during which the target is vulnerable allows one to determine if the target can be held at risk. Frequently, this is done using fixed estimates for the kill chain steps and target vulnerability time, thus providing a binary assessment. This paper formulates the problem probabilistically using known, estimated, or hypothesized probability distributions that capture the uncertainty in one’s knowledge about the kill chain timelines and the target’s vulnerability time. This approach provides a nonbinary estimate of the likelihood that a time-sensitive target can be held at risk and provides the means for performing sensitivity analysis to estimate the benefit of temporal improvements in each step of the kill chain.

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