6 papers
Privacy-preserving Chunk Scheduling in a BitTorrent Implementation of Federated Learning
Naicheng Li, Javad Dogani, Rui Wang +2
Traditional federated learning (FL) relies on a central aggregator server, which can create performance bottlenecks and privacy risks. Decentralized mix-and-forward designs remove…
DETOUR: A Practical Backdoor Attack against Object Detection
Dazhuang Liu, Yanqi Qiao, Rui Wang +2
Object detection (OD) is critical to real-world vision systems, yet existing backdoor attacks on detection transformers (DETRs) for OD tasks rely on patch-wise triggers optimized a…
PASTA: A Patch-Agnostic Twofold-Stealthy Backdoor Attack on Vision Transformers
Dazhuang Liu, Yanqi Qiao, Rui Wang +2
Vision Transformers (ViTs) have achieved remarkable success across vision tasks, yet recent studies show they remain vulnerable to backdoor attacks. Existing patch-wise attacks typ…
LADDER: Multi-objective Backdoor Attack via Evolutionary Algorithm
Dazhuang Liu, Yanqi Qiao, Rui Wang +2
Current black-box backdoor attacks in convolutional neural networks formulate attack objective(s) as single-objective optimization problems in single domain. Designing triggers in…
Low-Frequency Black-Box Backdoor Attack via Evolutionary Algorithm
Yanqi Qiao, Dazhuang Liu, Rui Wang +1
While convolutional neural networks (CNNs) have achieved success in computer vision tasks, it is vulnerable to backdoor attacks. Such attacks could mislead the victim model to make…
FTA: Stealthy and Adaptive Backdoor Attack with Flexible Triggers on Federated Learning
Yanqi Qiao, Dazhuang Liu, Congwen Chen +2
Current backdoor attacks against federated learning (FL) strongly rely on universal triggers or semantic patterns, which can be easily detected and filtered by certain defense mech…