3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.LG2019★ 3 cited
Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions
He Zhao, Trung Le, Paul Montague +3
Deep neural network image classifiers are reported to be susceptible to adversarial evasion attacks, which use carefully crafted images created to mislead a classifier. Recently, v…
stat.ML2019
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence
Yi Han, David Hubczenko, Paul Montague +6
Recent studies have demonstrated that reinforcement learning (RL) agents are susceptible to adversarial manipulation, similar to vulnerabilities previously demonstrated in the supe…
cs.CR2018
Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham +6
Despite the successful application of machine learning (ML) in a wide range of domains, adaptability---the very property that makes machine learning desirable---can be exploited by…