Modeling and Optimizing the Performance-Security Tradeoff on D-NCS Using the Coevolutionary Paradigm

Abstract

Distributed networked control systems (D-NCS) are vulnerable to various network attacks when the network is not secured; thus, D-NCS must be well protected with security mechanisms (e.g., cryptography), which may adversely affect the dynamic performance of the D-NCS because of limited system resources. This paper addresses the tradeoff between D-NCS security and its real-time performance and uses the Intelligent Space (iSpace) for illustration. A tradeoff model for a system's dynamic performance and its security is presented. This model can be used to allocate system resources to provide sufficient protection and to satisfy the D-NCS's real-time dynamic performance requirements simultaneously. Then, the paper proposes a paradigm of the performance-security tradeoff optimization based on the coevolutionary genetic algorithm (CGA) for D-NCS. A Simulink-based test-bed is implemented to illustrate the effectiveness of this paradigm. The results of the simulation show that the CGA can efficiently find the optimal values in a performance-security tradeoff model for D-NCS.