# Robust and Efficient AI-Based Attack Recovery in Autonomous Drones

arXiv: https://arxiv.org/abs/2505.14835 · HTML: https://mlsanity.com/paper/2505.14835/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 May 2025.

## Built on by (most cited first, 3 of 3)

- [CHAI: Command Hijacking against embodied AI](https://mlsanity.com/paper/2510.00181/) (2025)
- [Drones that Think on their Feet: Sudden Landing Decisions with Embodied AI](https://mlsanity.com/paper/2510.00167/) (2025)
- [Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site Assessment](https://mlsanity.com/paper/2510.22204/) (2025)

## Abstract (arXiv)

We introduce an autonomous attack recovery architecture to add common sense reasoning to plan a recovery action after an attack is detected. We outline use-cases of our architecture using drones, and then discuss how to implement this architecture efficiently and securely in edge devices.