Detecting Model-Poisoning Attacks in Federated Healthcare Learning

Problem statement

Federated healthcare models can be manipulated when some simulated hospitals send poisoned or label-flipped model updates.

Objective

Evaluate whether robust aggregation methods can protect a federated healthcare model as the share of malicious clients increases.

Student focus

  • Federated learning
  • Attacks/defenses
  • Healthcare simulation
Tags: Cybersecurity, Cyberphysical
Published Oct. 13, 2026 11:38 AM - Last modified Oct. 13, 2026 11:38 AM

Supervisor(s)

Scope (credits)

30