4 papers
Modeling Spectral Energy Shifts in Spatio-Temporal Graph Anomaly Detection
Yilin Liu, Hongchao Zhang, Taylor T. Johnson +2
Graph anomaly detection methods aim to distinguish anomalous nodes. While prior methods characterize anomalies through increased variation in the spectral energy distributions, the…
LOGSAFE: Logic-Guided Verification for Trustworthy Federated Time-Series Learning
Dung Thuy Nguyen, Ziyan An, Taylor T. Johnson +2
This paper introduces LOGSAFE, a defense mechanism for federated learning in time series settings, particularly within cyber-physical systems. It addresses poisoning attacks by mov…
PBP: Post-training Backdoor Purification for Malware Classifiers
Dung Thuy Nguyen, Ngoc N. Tran, Taylor T. Johnson +1
In recent years, the rise of machine learning (ML) in cybersecurity has brought new challenges, including the increasing threat of backdoor poisoning attacks on ML malware classifi…
PARDON: Privacy-Aware and Robust Federated Domain Generalization
Dung Thuy Nguyen, Taylor T. Johnson, Kevin Leach
Federated Learning (FL) shows promise in preserving privacy and enabling collaborative learning. However, most current solutions focus on private data collected from a single domai…