108 research outputs found
Combating False Reports for Secure Networked Control in Smart Grid via Trustiness Evaluation
Smart grid, equipped with modern communication infrastructures, is subject to
possible cyber attacks. Particularly, false report attacks which replace the
sensor reports with fraud ones may cause the instability of the whole power
grid or even result in a large area blackout. In this paper, a trustiness
system is introduced to the controller, who computes the trustiness of
different sensors by comparing its prediction, obtained from Kalman filtering,
on the system state with the reports from sensor. The trustiness mechanism is
discussed and analyzed for the Linear Quadratic Regulation (LQR) controller.
Numerical simulations show that the trustiness system can effectively combat
the cyber attacks to smart grid.Comment: It has been submitted to IEEE International Conference on
Communications (ICC
Statistical Watermarking for Networked Control Systems
Watermarking can detect sensor attacks in control systems by injecting a
private signal into the control, whereby attacks are identified by checking the
statistics of the sensor measurements and private signal. However, past
approaches assume full state measurements or a centralized controller, which is
not found in networked LTI systems with subcontrollers. Since generally the
entire system is neither controllable nor observable by a single subcontroller,
communication of sensor measurements is required to ensure closed-loop
stability. The possibility of attacking the communication channel has not been
explicitly considered by previous watermarking schemes, and requires a new
design. In this paper, we derive a statistical watermarking test that can
detect both sensor and communication attacks. A unique (compared to the
non-networked case) aspect of the implementing this test is the state-feedback
controller must be designed so that the closed-loop system is controllable by
each sub-controller, and we provide two approaches to design such a controller
using Heymann's lemma and a multi-input generalization of Heymann's lemma. The
usefulness of our approach is demonstrated with a simulation of detecting
attacks in a platoon of autonomous vehicles. Our test allows each vehicle to
independently detect attacks on both the communication channel between vehicles
and on the sensor measurements
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