8 papers
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…
Mitigating Adversarial Effects of False Data Injection Attacks in Power Grid
Farhin Farhad Riya, Shahinul Hoque, Yingyuan Yang +3
Deep Neural Networks have proven to be highly accurate at a variety of tasks in recent years. The benefits of Deep Neural Networks have also been embraced in power grids to detect…
Deep Learning model integrity checking mechanism using watermarking technique
Shahinul Hoque, Farhin Farhad Riya, Yingyuan Yang +1
In response to the growing popularity of Machine Learning (ML) techniques to solve problems in various industries, various malicious groups have started to target such techniques i…
Effects of Real-Life Traffic Sign Alteration on YOLOv7- an Object Recognition Model
Farhin Farhad Riya, Shahinul Hoque, Md Saif Hassan Onim +3
The widespread adoption of Image Processing has propelled Object Recognition (OR) models into essential roles across various applications, demonstrating the power of AI and enablin…