SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning

no code implementations • 11 Jan 2023 • Maxwell Standen, Junae Kim, Claudia Szabo

Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications.

Multi-agent Reinforcement Learning reinforcement-learning +1

Deep hierarchical reinforcement agents for automated penetration testing

no code implementations • 14 Sep 2021 • Khuong Tran, Ashlesha Akella, Maxwell Standen, Junae Kim, David Bowman, Toby Richer, Chin-Teng Lin

Penetration testing the organised attack of a computer system in order to test existing defences has been used extensively to evaluate network security.

Q-Learning