14 citations · 47 across the 18 of their papers we have counts for
4 papers · 1 filter
TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
In Federated Learning, clients train models on local data and send updates to a central server, which aggregates them into a global model using a fusion algorithm. This collaborati…
FedDefender: Backdoor Attack Defense in Federated Learning
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
Federated Learning (FL) is a privacy-preserving distributed machine learning technique that enables individual clients (e.g., user participants, edge devices, or organizations) to…
Blocking JavaScript without Breaking the Web: An Empirical Investigation
Abdul Haddi Amjad, Zubair Shafiq, Muhammad Ali Gulzar
Modern websites heavily rely on JavaScript (JS) to implement legitimate functionality as well as privacy-invasive advertising and tracking. Browser extensions such as NoScript bloc…
FedDebug: Systematic Debugging for Federated Learning Applications
Waris Gill, Ali Anwar, Muhammad Ali Gulzar
In Federated Learning (FL), clients independently train local models and share them with a central aggregator to build a global model. Impermissibility to access clients' data and…