Review Article
Survey of Attack Graph Analysis Methods from the Perspective of Data and Knowledge Processing
Table 4
Comparison of attack graph analysis methods.
| Analysis method | Advantage | Disadvantage | Calculation tasks | Complexity | Scalability |
| Graph algorithm | Intuitive, portable | Insufficient combination with exploit utilization | Identify the most likely path and high-risk node, predict attack behavior | O(n2) | Strong |
| Bayesian network | Flexible, easy to train | Complicated analytical calculations | Analyze vulnerability, identify high-risk nodes, network hardening, and predict attack behavior | O(n2) | General |
| Markov model | Easy to train, better prediction | More restrictions | Identify the most likely paths, identify high-risk nodes, network hardening, and predict attack behavior | O(n2) | General |
| Cost optimization algorithm | | | | | | Game theory | Strong portability | Slight discrepancy with actual results | Network hardening, predict attack behavior | O(n2) | General | Cost minimization algorithm | Strong portability | Limited application, difficult model selection | Network hardening, predict attack behavior | O(n) | Strong |
| Uncertainty algorithm | Solved problems that other algorithms cannot solve | Limited application areas | Analyze vulnerability, identify high-risk nodes | — | Strong |
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