2 citations · 2 across the 4 of their papers we have counts for
4 papers
Adversary Aware Continual Learning
Muhammad Umer, Robi Polikar
Class incremental learning approaches are useful as they help the model to learn new information (classes) sequentially, while also retaining the previously acquired information (c…
Contributor-Aware Defenses Against Adversarial Backdoor Attacks
Glenn Dawson, Muhammad Umer, Robi Polikar
Deep neural networks for image classification are well-known to be vulnerable to adversarial attacks. One such attack that has garnered recent attention is the adversarial backdoor…
False Memory Formation in Continual Learners Through Imperceptible Backdoor Trigger
Muhammad Umer, Robi Polikar
In this brief, we show that sequentially learning new information presented to a continual (incremental) learning model introduces new security risks: an intelligent adversary can…
Targeted Forgetting and False Memory Formation in Continual Learners through Adversarial Backdoor Attacks
Muhammad Umer, Glenn Dawson, Robi Polikar
Artificial neural networks are well-known to be susceptible to catastrophic forgetting when continually learning from sequences of tasks. Various continual (or "incremental") learn…