Intrusion Tolerance for Networked Systems through Two-Level Feedback Control
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Abstract (arXiv)
We formulate intrusion tolerance for a system with service replicas as a two-level optimal control problem. On the local level node controllers perform intrusion recovery, and on the global level a system controller manages the replication factor. The local and global control problems can be formulated as classical problems in operations research, namely, the machine replacement problem and the inventory replenishment problem. Based on this formulation, we design TOLERANCE, a novel control architecture for intrusion-tolerant systems. We prove that the optimal control strategies on both levels have threshold structure and design efficient algorithms for computing them. We implement and evaluate TOLERANCE in an emulation environment where we run 10 types of network intrusions. The results show that TOLERANCE can improve service availability and reduce operational cost compared with state-of-the-art intrusion-tolerant systems.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 22 of its 153 references that are in the map. First posted on arXiv 2 Apr 2024.
Builds on
22 of 153 references.
References · 22
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10 more
- 2024Conjectural Online Learning with First-order Beliefs in Asymmetric Information Stochastic Gamescited by 14
- 2023Learning Near-Optimal Intrusion Responses Against Dynamic Attackerscited by 13
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Citing papers per year: 2024: 1; 2025: 3; 2026: 4.
8 papers.
- 2024Optimal Defender Strategies for CAGE-2 using Causal Modeling and Tree Searchcited by 12
- 2025SoK: Trust-Authorization Mismatch in LLM Agent Interactionscited by 11
- 2025Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucinationcited by 10
- 2025Online Incident Response Planning under Model Misspecification through Bayesian Learning and Belief Quantizationcited by 5
- 2026CSLE: A Reinforcement Learning Platform for Autonomous Security Managementcited by 5
- 2026In-Context Autonomous Network Incident Response: An End-to-End Large Language Model Agent Approachcited by 4
- 2026Hallucination-Resistant Security Planning with a Large Language Modelcited by 1
- 2026The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphscited by 0
- 2026The MAL Simulator: Cyber Operations Simulation based on Attack & Defense Graphs15 Sep 2026
- 2026CSLE: A Reinforcement Learning Platform for Autonomous Security Management16 Apr 2026
- 2026In-Context Autonomous Network Incident Response: An End-to-End Large Language Model Agent Approach13 Feb 2026
- 2026Hallucination-Resistant Security Planning with a Large Language Model5 Feb 2026
- 2025SoK: Trust-Authorization Mismatch in LLM Agent Interactions7 Dec 2025
- 2025Online Incident Response Planning under Model Misspecification through Bayesian Learning and Belief Quantization20 Aug 2025
- 2025Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucination7 Aug 2025
- 2024Optimal Defender Strategies for CAGE-2 using Causal Modeling and Tree Search12 Jul 2024