2 citations · 6 across the 7 of their papers we have counts for
8 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…
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…
Smart Driver Monitoring Robotic System to Enhance Road Safety : A Comprehensive Review
Farhin Farhad Riya, Shahinul Hoque, Xiaopeng Zhao +1
The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infra…
HRI Challenges Influencing Low Usage of Robotic Systems in Disaster Response and Rescue Operations
Shahinul Hoque, Farhin Farhad Riya, Jinyuan Sun
The breakthrough in AI and Machine Learning has brought a new revolution in robotics, resulting in the construction of more sophisticated robotic systems. Not only can these roboti…
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…
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…