  We address the problem of robust state reconstruction for discrete-time
nonlinear systems when the actuators and sensors are injected with (potentially
unbounded) attack signals. Exploiting redundancy in sensors and actuators and
using a bank of unknown input observers (UIOs), we propose an observer-based
estimator capable of providing asymptotic estimates of the system state and
attack signals under the condition that the numbers of sensors and actuators
under attack are sufficiently small. Using the proposed estimator, we provide
methods for isolating the compromised actuators and sensors. Numerical examples
are provided to demonstrate the effectiveness of our methods.
