Adversarial Learning-Based On-Line Anomaly Monitoring for Assured Autonomy

12 Nov 2018Naman PatelApoorva Nandini SaridenaAnna ChoromanskaPrashanth KrishnamurthyFarshad Khorrami

The paper proposes an on-line monitoring framework for continuous real-time safety/security in learning-based control systems (specifically application to a unmanned ground vehicle). We monitor validity of mappings from sensor inputs to actuator commands, controller-focused anomaly detection (CFAM), and from actuator commands to sensor inputs, system-focused anomaly detection (SFAM)... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper