# Improvise, Adapt, Overcome: Dynamic Resiliency Against Unknown Attack Vectors in Microgrid Cybersecurity Games

arXiv: https://arxiv.org/abs/2306.15106 · HTML: https://mlsanity.com/paper/2306.15106/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jun 2023.

## Built on by (most cited first, 1 of 1)

- [Data-Driven Graph Switching for Cyber-Resilient Control in Microgrids](https://mlsanity.com/paper/2411.07686/) (2024)

## Abstract (arXiv)

Cyber-physical microgrids are vulnerable to rootkit attacks that manipulate system dynamics to create instabilities in the network. Rootkits tend to hide their access level within microgrid system components to launch sudden attacks that prey on the slow response time of defenders to manipulate system trajectory. This problem can be formulated as a multi-stage, non-cooperative, zero-sum game with the attacker and the defender modeled as opposing players. To solve the game, this paper proposes a deep reinforcement learning-based strategy that dynamically identifies rootkit access levels and isolates incoming manipulations by incorporating changes in the defense plan. A major advantage of the proposed strategy is its ability to establish resiliency without altering the physical transmission/distribution network topology, thereby diminishing potential instability issues. The paper also presents several simulation results and case studies to demonstrate the operating mechanism and robustness of the proposed strategy.