Model Predictive Control with adaptive resilience for Denial-of-Service Attacks mitigation on a Regulated Dam
원문 초록
In recent years, SCADA (Supervisory Control and Data Acquisition) systems have increasingly become the target of cyber attacks. SCADAs are no longer isolated, as web-based applications expose strategic infrastructures to the outside world connection. In a cyber-warfare context, we propose a Model Predictive Control (MPC) architecture with adaptive resilience, capable of guaranteeing control performance in normal operating conditions and driving towards resilience against DoS (controller-actuator) attacks when needed. Since the attackers' goal is typically to maximize the system damage, we assume they solve an adversarial optimal control problem. An adaptive resilience factor is then designed as a function of the intensity function of a Hawkes process, a point process model estimating the occurrence of random events in time, trained on a moving window to estimate the return time of the next attack. We demonstrate the resulting MPC strategy's effectiveness in 2 attack scenarios on a real system with actual data, the regulated Olginate dam of Lake Como.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Differentiable Nonlinear Model Predictive Control
Evaluating the Impact of Model Accuracy for Optimizing Battery Energy Storage Systems
Re4MPC: Reactive Nonlinear MPC for Multi-model Motion Planning via Deep Reinforcement Learning
Deep Operator Neural Network Model Predictive Control
Knot So Simple: A Minimalistic Environment for Spatial Reasoning
Efficient Configuration-Constrained Tube MPC via Variables Restriction and Template Selection
토론
이 논문과 연결된 포럼 글이 아직 없습니다.