9 citations · 15 across the 25 of their papers we have counts for
6 papers · 1 filter
Synthesis Without Training: An Inference-Only Pipeline for Tabular, Temporal, and Relational Synthetic Data
Zilong Zhao, Abdul Raheem, Jiayu Li +5
Synthetic data generation is dominated by the fit-then-sample paradigm: a generative model is trained on a private dataset and then sampled from. Despite its widespread adoption, t…
CDN Tsunami: Exploiting HTTP/3-HTTP/1.1 Conversion for DoS Attacks
Ziyu Lin, Tianlong Su, Yingjie Lin +4
Content Delivery Networks (CDNs) provide high availability, accelerate content delivery for their host websites, but are also vulnerable to different types of Denial-of-Service (Do…
Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting
Yi Li, Han Liu, Mingfeng Fan +3
Federated learning (FL) on graphs shows promise for distributed time-series forecasting. Yet, existing methods rely on static topologies and struggle with client heterogeneity. We…
PEANUT: Perturbations by Eigenvector Alignment for Attacking Graph Neural Networks Under Topology-Driven Message Passing
Bhavya Kohli, Biplab Sikdar
Message Passing Neural Networks (MPNNs) have achieved strong performance on tasks involving relational data. However, small perturbations to graph structure can significantly alter…
Baiting AI: Deceptive Adversary Against AI-Protected Industrial Infrastructures
Aryan Pasikhani, Prosanta Gope, Yang Yang +2
This paper explores a new cyber-attack vector targeting Industrial Control Systems (ICS), particularly focusing on water treatment facilities. Developing a new multi-agent Deep Rei…
Unified Framework for Qualifying Security Boundary of PUFs Against Machine Learning Attacks
Hongming Fei, Zilong Hu, Prosanta Gope +1
Physical Unclonable Functions (PUFs) serve as lightweight, hardware-intrinsic entropy sources widely deployed in IoT security applications. However, delay-based PUFs are vulnerable…