DecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning

arXiv:2609.36330 · cs.CR, cs.AI · Submitted 2026-09-28 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/pedrobeltranl/nebula

Terminology

• Aggregation — 34× in this paper · explained in 1 episode
• Federated Learning — 24× in this paper · explained in 14 episodes
• Verification — 15× in this paper · explained in 2 episodes
• Decentralized Federated Learning — 10× in this paper · explained in 2 episodes
• Robustness — 8× in this paper · explained in 5 episodes
• Honesty Rate — 5× in this paper
• Consistency — 4× in this paper · explained in 3 episodes
• Trace — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Depth-First Search — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Artificial Intelligence — 2× in this paper
• Internet of Things — 2× in this paper
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Model — 1× in this paper · explained in 1 episode
• Arbiter — 1× in this paper · explained in 1 episode
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Chaotic Dynamics — 1× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Federated Learning (FL) — 1× in this paper · explained in 7 episodes
• Local Optimization — 1× in this paper · explained in 2 episodes
• Non-IID Data — 1× in this paper · explained in 2 episodes
• Suspicious Rate — 1× in this paper
• Transferability — 1× in this paper · explained in 4 episodes

Sources

• Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
• Federated Learning with Non-IID Data
• Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification

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