Abstract
Intrusion Detection Systems (IDS) are security tools that aim to detect tentative of virus propagation between two interconnected devices. As the propagation of a virus or malware is dynamic and can be strategically controlled by the attacker, we model the problem of optimally determining IDS position in a network as a partially observable zero-sum stochastic Minimum-Threat path game (POSMPG). The goal of the attacker is to infect a maximum number of nodes at a given instant, and then a state-extended stochastic game framework is proposed in order to get optimality equations. We are then able to determine optimal solutions of the POSMPG and to apply our result to an adversarial control of virus propagation on a network.
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Notes
- 1.
The reward of player 2 is assumed positive in [20].
- 2.
In the case of epidemic for example, \(\varphi \left( z\right) \) is the number of infected nodes in state z.
- 3.
One can take \(S^{\gamma }_{N} = S \times \mathbbm {N}\).
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Acknowledgments
Research was sponsored by the U.S. Army Research Office and was accomplished under Cooperative Agreement Number W911NF-22-2-0175 and Grant Number W911NF-21-1-0326. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.
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Tsemogne, O., Hayel, Y., Kamhoua, C., Deugoué, G. (2023). Optimizing Intrusion Detection Systems Placement Against Network Virus Spreading Using a Partially Observable Stochastic Minimum-Threat Path Game. In: Fang, F., Xu, H., Hayel, Y. (eds) Decision and Game Theory for Security. GameSec 2022. Lecture Notes in Computer Science, vol 13727. Springer, Cham. https://doi.org/10.1007/978-3-031-26369-9_14
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