"FedWave: Code and Evaluation Logs for Stealthy Wavelet-Domain Backdoor Attacks in Federated Learning"

Abstract

"This dataset contains the source code and evaluation logs supporting the manuscript \"FedWave: Stealthy Wavelet-Domain Backdoor Attacks in Federated Learning,\" submitted to the IEEE Transactions on Information Forensics and Security.FedWave is an anchor-aligned wavelet-subband backdoor framework for federated learning (FL). It combines three mechanisms: (i) frequency-domain trigger embedding in the LH\/HL\/HH subbands of a one-level 2D Haar DWT, restricted to the blue channel for visual stealth; (ii) subband-wise trigger decomposition with probabilistic cross-client association, governed by an association probability p; and (iii) Anchor-Based Projection (ABP), which aligns each poisoned update to a safety band centred on a locally simulated, same-round benign update norm.The release includes the FedWave implementation, the baseline attack implementations used for comparison (BadNets, DBA, FIBA-FL, Neurotoxin), the evaluation harness for the nine defenses studied in the manuscript, and the per-round metric logs from which every table and figure is produced. All experiments use ResNet-18 on CIFAR-10 and GTSRB and a lightweight SimpleCNN on EMNIST, under Dirichlet non-IID client partitioning.The input datasets (CIFAR-10, GTSRB, EMNIST) are third-party public resources and are NOT redistributed here; links to their official sources are provided under Links. These artifacts are released to support reproducibility and follow-on defense research. See README for responsible-use terms. "