  A cyber-physical system (CPS) is a tight coupling of computational resources,
network communication, and physical processes. They are composed of a set of
networked components, including sensors, actuators, control processing units,
and communication agents that instrument the physical world to make smarter.
However, cyber components are also the source of new, unprecedented
vulnerabilities to malicious attacks. In order to protect a CPS from attacks,
three security levels of protection, detection, and identification are
considered. In this chapter, we will discuss the identification level, i.e.,
secure state estimation and attack reconstruction of CPS with corrupted states
and measurements. Considering different attack plans that may assault the
states, sensors, or both of them, different online attack reconstruction
approaches are discussed. Fixed-gain and adaptive-gain finite-time convergent
observation algorithms, specifically sliding mode observers, are applied to the
online reconstruction of sensor and state attacks. Next, the corrupted
measurements and states are to be cleaned up online in order to stop the attack
propagation to the CPS via the control signal. The proposed methodologies are
applied to an electric power network, whose states and sensors are under
attack. Simulation results illustrate the efficacy of the proposed observers.
