4 papers
IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning
Farhin Farhad Riya, Olivera Kotevska, Jinyuan Stella Sun
Heterogeneous Differential Privacy (HDP) in Federated Learning (FL) allows clients to select individual privacy budgets () according to institutional policies and da…
Pseudo-Feature Padding: A Lightweight Defense Against False Data Injection in Power Grids
Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +2
Deep Neural Networks DNNs have achieved remarkable accuracy in various tasks including their application in CyberPhysical Systems CPS for detecting False Data Injection Attacks FDI…
Token Inflation: How Dishonest Providers Can Overcharge for Large Language Model Usage
Shahinul Hoque, Jinghuai Zhang, Jinyuan Sun +1
Per-token billing is now the standard pricing model for commercial large language models (LLMs), so the honesty of reported token counts directly affects what users pay. We show th…
Accuracy is Not Enough: Poisoning Interpretability in Federated Learning via Color Skew
Farhin Farhad Riya, Shahinul Hoque, Jinyuan Stella Sun +1
As machine learning models are increasingly deployed in safety-critical domains, visual explanation techniques have become essential tools for supporting transparency. In this work…