byzantine-robustness

Research testbed for federated learning with hybrid quantum-classical models and post-quantum protection (ML-KEM, ML-DSA, secure aggregation). Reproducible results: a 4-qubit VQC head vs a matched classical head, robust aggregation vs poisoning, PQC cost per round. PennyLane, PyTorch, Flower, FastAPI.

Federated learning + secure aggregation + zero-knowledge norm-bound defence

Federated learning sentiment analysis with AT-FedAvg — adaptive trust-aware aggregation across IMDB, Sentiment140 & Amazon. BiLSTM · PyTorch · Flower · FastAPI · Streamlit

Asynchronous Byzantine-Robust Federated Learning with Layer-Stratified Subspace Filtering and Behavioral Memory under Extreme Non-IID Skew.

A bank-agnostic fraud-intelligence layer that learns risk thresholds across banks without any bank sharing its data — with the evaluation that says exactly how far that claim has been tested.

Decentralized Continual Cyber Defense: Federated Continual Learning (FCL) for Encrypted Traffic Intrusion Detection with Byzantine Robustness and Differential Privacy

Information-theoretic framework for measuring trust in AI systems. Code accompanying Dong (2026), Communications AI & Computing.

Cross-silo federated learning on Fed-ISIC2019 (6 real hospital centres): FedAvg/FedProx/SCAFFOLD/FedAdam, DP-SGD with an independent RDP accountant, membership-inference and poisoning attacks, secure + robust aggregation, 50x update compression, and a real Raspberry Pi 5 edge client over Flower/gRPC.

FUSE federated-learning Byzantine screening: faithful reimplementation with a 128-run audit grid across 7 attacks (sign-flip, IPM, Gaussian, ALIE, Min-Max, Min-Sum, magnitude scaling)

Reproducible TDAW research lab for history-aware Byzantine-robust federated MNIST training, with a Rust core, Flower modes, and a Next.js dashboard.

Decentralized federated reinforcement learning with gossip, ADMM consensus and Byzantine robustness

Deterministic fixed-point Byzantine-robust aggregation receipts with explicit coordinate witnesses and independent pairwise-rank replay.

Certified Byzantine robustness for model-heterogeneous federated learning: ensemble subsets + robust distillation aggregation with honest certificates

Research prototype for centralized and simulated federated intrusion detection, with hierarchical classification and an explainable pretrained replay demo.

Topology-adaptive Byzantine defense for decentralized federated learning — the defense that adapts to your network, not the other way around

Plug-and-play MNIST library for adversarial ML: evasion attacks, backdoor attacks and defenses, and Byzantine-robust federated learning.

Eight-peer Adult benchmark of non-IID learning, poisoned updates, robust aggregation and membership auditing.

Train one machine-learning model across many parties who don't trust each other. A dishonest minority can't skew the result, and every party computes byte-for-byte identical output on any CPU or architecture (big-endian included) — so each round ships a receipt anyone can re-check offline and reproduce exactly. Rust; drop-in for Flower.

Code, tests and per-run results for Post-Quantum Byzantine-Resilient Federated Learning for SDN Intrusion Detection