Probabilistic attack-aware learning and multi-model inference for distributed state estimation under hybrid DoS and FDI attacks

2026-06-09

PRE

Xuemei Mao

Jiacheng He

Gang Wang

Mingzhu Wei

Bei Peng *

DOI：10.1016/j.conengprac.2026.107102

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• PALM-DKF enables distributed nonlinear estimation under hybrid attacks. • Receiver-side learning models link-wise packet uncertainty online. • Multi-regime DUKF propagates learned attack-induced uncertainty. • DoS-aware CI fusion improves agreement without cross-covariances. • Top-K pruning balances accuracy and computational complexity.

Probabilistic attack-aware learning and multi-model inference for distributed state estimation under hybrid DoS and FDI attacks

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