4 papers · 1 filter
Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
Kunal Mukherjee, Zulfikar Alom, Tran Gia Bao Ngo +2
The rise of bot accounts on social media poses significant risks to public discourse. To address this threat, modern bot detectors increasingly rely on Graph Neural Networks (GNNs)…
FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments
Anik Pramanik, Murat Kantarcioglu, Vincent Oria +1
Federated Learning (FL) enables a group of clients to collaboratively train a model without sharing individual data, but its performance drops when client data are heterogeneous. C…
Learning Joint Embeddings of Function and Process Call Graphs for Malware Detection
Kartikeya Aneja, Nagender Aneja, Murat Kantarcioglu
Software systems can be represented as graphs, capturing dependencies among functions and processes. An interesting aspect of software systems is that they can be represented as di…
PROVCREATOR: Synthesizing Complex Heterogenous Graphs with Node and Edge Attributes
Tianhao Wang, Simon Klancher, Kunal Mukherjee +4
The rise of graph-structured data has driven interest in graph learning and synthetic data generation. While successful in text and image domains, synthetic graph generation remain…