Distributed Resilient Filtering for Power Systems Subject to Denial-of-Service Attacks

TLDR

The study tackles distributed resilient filtering for power systems under denial‑of‑service attacks. A novel distributed filter is designed that accounts for DoS attacks and gain perturbations, with error‑covariance bounds derived and filter gains computed via Riccati‑like equations solved by a gradient‑based method, yielding a recursive implementation. The resulting recursive filter operates without global information, ensuring scalability and online distributed implementation.

Abstract

This paper addresses the distributed resilient filtering problem for a class of power systems subject to denial-of-service (DoS) attacks. A novel distributed filter is first constructed to practically reflect the impact from both cyber-attacks and gain perturbations. For all possible occurrence of DoS attacks and gain perturbations, an upper bound of filtering error covariance is derived by resorting to some typical matrix inequalities. Furthermore, the desired filter gain relying on the solution of two Riccati-like difference equations is obtained with the help of the gradient-based approach and the mathematical induction. The developed algorithm with a recursive form is independent of the global information and thus satisfies the requirements of scalability and distributed implementation online. Finally, a benchmark simulation test is exploited to check the usefulness of the designed filter.