Tolerating Adversaries in the Estimation of Network Parameters from Noisy Data: A Nonlinear Filtering Approach

Estimating network parameters from noisy data is a hard problem that can be made even more difficult by the presence of a malicious adversary who may corrupt the measurement process by capturing a trusted node or perturbing data externally. The adversary may have complete knowledge of the networking protocols that rely on the parameter estimates and may adjust its effect on the system to push protocols into incorrect operating regimes.

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