Robust and Efficient AI-Based Attack Recovery in Autonomous Drones

TL;DR

This paper presents an autonomous attack recovery system for drones that uses common sense reasoning to plan recovery actions, aiming for efficiency and security in edge device implementation.

Contribution

It introduces a novel architecture integrating common sense reasoning for attack recovery in autonomous drones, emphasizing efficiency and security in edge deployment.

Findings

Effective attack detection and recovery planning in drones

Secure and efficient implementation on edge devices

Use-case demonstrations of the architecture

Abstract

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.