Research map / Graph learning / Graph algorithms and clustering
Practical Fixed-Parameter Algorithms for Defending Active Directory Style Attack Graphs
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use BudgetFPT instead of Greedy | Active Directory edge interdiction · r2000, b=10, s=5 | Success Rate: 0.483 -> 0.308 | Helped |
| Use GCN instead of Greedy | Active Directory edge interdiction · r2000, b=10, s=5 | Success Rate: 0.483 -> 0.324 | Helped |
| Use DP instead of Greedy | Active Directory edge interdiction · r2000-dag, b=10, s=5 | Success Rate: 0.449 -> 0.449 | No clear effect |
| Add substitutable blockable edges | r2000-dag · Acyclic setting with substitutable edges, b=10, s=5 | Success Rate: Greedy: 0.449 -> 0.566; DP: 0.449 -> 0.465 | Mixed |
| Use DP instead of Greedy | Active Directory edge interdiction · r2000-dag with substitutable edges, b=10, s=5 | Success Rate: 0.566 -> 0.465 | Helped |
| Use GCN instead of Greedy | Active Directory edge interdiction · r2000-dag with substitutable edges, b=10, s=5 | Success Rate: 0.566 -> 0.465 | Helped |
| Raise the blockable-edge probability from p_b=0.2 to p_b=0.4 | GCN and Greedy · r2000, b=20, s=10 | Success Rate: GCN: 0.450 -> 0.226; Greedy: 0.438 -> 0.287 | Helped |
| Use GCN instead of Greedy | Active Directory edge interdiction · r2000, b=20, s=10, p_b=0.2 | Success Rate: 0.438 -> 0.450 | Hurt |
| Use GCN instead of Greedy | Active Directory edge interdiction · r2000, b=20, s=10, p_b=0.4 | Success Rate: 0.287 -> 0.226 | Helped |
Closest papers by meaning
- Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs (AAAI 2023 · similarity 0.94)
- Defending with Shared Resources on a Network (AAAI 2020 · similarity 0.83)
- Limited Query Graph Connectivity Test (AAAI 2024 · similarity 0.82)
- Robustness Inspired Graph Backdoor Defense (ICLR 2025 · similarity 0.82)
- Highly Imperceptible Black-Box Graph Injection Attacks with Reinforcement Learning (AAAI 2025 · similarity 0.80)
- Privacy Attacks in Decentralized Learning (ICML 2024 · similarity 0.80)
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