Physics-Attested Federated Learning: Securing Collaborative Anomaly Detection in Critical Water Infrastructure

arXiv:2609.34804 · cs.CR, cs.LG · Submitted 2026-09-28 · Read on arXiv

cs.CR, cs.LG

Submitted: 2026-09-28

Updated: 2026-09-28

Code: https://github.com/icsdataset/hai

Terminology

• Aggregation — 75× in this paper · explained in 1 episode
• Federated Learning — 26× in this paper · explained in 16 episodes
• Verification — 22× in this paper · explained in 2 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Verifier — 6× in this paper · explained in 2 episodes
• Reconstruction Error — 5× in this paper · explained in 2 episodes
• Computer and Communications Security — 4× in this paper
• Calibration — 3× in this paper · explained in 7 episodes
• Provenance — 3× in this paper · explained in 4 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Adaptive Projection — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Physical Constraints — 2× in this paper · explained in 7 episodes
• System Identification — 2× in this paper · explained in 3 episodes
• Trace — 2× in this paper · explained in 2 episodes
• AUC — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Analyser Indicator Transmitters — 1× in this paper
• Benchmarking — 1× in this paper · explained in 4 episodes
• Conservation Laws — 1× in this paper · explained in 3 episodes
• Federated Learning (FL) — 1× in this paper · explained in 7 episodes
• Hardware-in-the-Loop Augmented ICS — 1× in this paper
• Network and Distributed System Security Symposium — 1× in this paper
• Singapore University of Technology and Design — 1× in this paper
• Symposium on High Assurance Systems Engineering — 1× in this paper
• Workshop on Decentralized IoT Systems and Security — 1× in this paper

Sources

• On Evaluating Adversarial Robustness
• Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching
• Benchmarking ZK-Friendly Hash Functions and SNARK Proving Systems for EVM-compatible Blockchains
• Can You Really Backdoor Federated Learning?
• Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm

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