# A Supervisory Control Approach to Dynamic Cyber-Security

arXiv: https://arxiv.org/abs/1409.0838 · HTML: https://mlsanity.com/paper/1409.0838/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Sep 2014.

## Built on by (most cited first, 5 of 5)

- [Intrusion Prevention through Optimal Stopping](https://mlsanity.com/paper/2111.00289/) (2021)
- [Learning Near-Optimal Intrusion Responses Against Dynamic Attackers](https://mlsanity.com/paper/2301.06085/) (2023)
- [Learning Intrusion Prevention Policies through Optimal Stopping](https://mlsanity.com/paper/2106.07160/) (2021)
- [Scalable Learning of Intrusion Responses through Recursive Decomposition](https://mlsanity.com/paper/2309.03292/) (2023)
- [Learning Security Strategies through Game Play and Optimal Stopping](https://mlsanity.com/paper/2205.14694/) (2022)

## Abstract (arXiv)

An analytical approach for a dynamic cyber-security problem that captures progressive attacks to a computer network is presented. We formulate the dynamic security problem from the defender's point of view as a supervisory control problem with imperfect information, modeling the computer network's operation by a discrete event system. We consider a min-max performance criterion and use dynamic programming to determine, within a restricted set of policies, an optimal policy for the defender. We study and interpret the behavior of this optimal policy as we vary certain parameters of the supervisory control problem.