3 papers
cs.CR2025
Evaluating Query Efficiency and Accuracy of Transfer Learning-based Model Extraction Attack in Federated Learning
Sayyed Farid Ahamed, Sandip Roy, Soumya Banerjee +6
Federated Learning (FL) is a collaborative learning framework designed to protect client data, yet it remains highly vulnerable to Intellectual Property (IP) threats. Model extract…
cs.LG2025
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining
Sam Pastoriza, Iman Yousfi, Christopher Redino +4
We propose a novel mechanism for real-time (human-in-the-loop) feedback focused on false positive reduction to enhance anomaly detection models. It was designed for the lightweight…
cs.LG2024
Privacy Drift: Evolving Privacy Concerns in Incremental Learning
Sayyed Farid Ahamed, Soumya Banerjee, Sandip Roy +6
In the evolving landscape of machine learning (ML), Federated Learning (FL) presents a paradigm shift towards decentralized model training while preserving user data privacy. This…