A Method of Kill Chains Fusion Based on Granulated Rules and Matrix Computation
Haijun Ye, Wei Gao · IEEE Access · 2024
Kill chains fusion based on the granulation rules and maintain the association information between the kill chains after the fusion is the focus of granularity research. Among these rules, this paper proposes a structured representation of kill chains in order to generate a weighted correlation structure supported by the weighting relationship. Furthermore, the conversion from the correlation structure to the granular structure based on damage probability is accomplished through the merged granulation set of kill chains. Firstly, a structural granulation method for kill chain merging is established using data to describe the transformation of kill chains in this paper. Then, the matrix computing formed the algorithmic foundation matrix of kill chains through granulation rules involving intermediate and target transformations. Finally, it was obtained that the combined kill chain significantly reduces the demand for resources such as time, missiles, and military aircraft through simulation experiments.