10th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

Research Article

Bio-inspired Active Attack for Identification of Networked Control Systems

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  • @INPROCEEDINGS{10.4108/eai.22-3-2017.152407,
        author={Alan Oliveira de Sa and Luiz Fernando Rust da Costa Carmo and Raphael Carlos Santos Machado},
        title={Bio-inspired Active Attack for Identification of Networked Control Systems},
        proceedings={10th EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)},
        publisher={EAI},
        proceedings_a={BICT},
        year={2017},
        month={3},
        keywords={security cyber-physical systems networked control systems system identification backtracking search algorithm particle swarm optimization},
        doi={10.4108/eai.22-3-2017.152407}
    }
    
  • Alan Oliveira de Sa
    Luiz Fernando Rust da Costa Carmo
    Raphael Carlos Santos Machado
    Year: 2017
    Bio-inspired Active Attack for Identification of Networked Control Systems
    BICT
    EAI
    DOI: 10.4108/eai.22-3-2017.152407
Alan Oliveira de Sa1,*, Luiz Fernando Rust da Costa Carmo2, Raphael Carlos Santos Machado2
  • 1: Brazilian Navy
  • 2: Inmetro
*Contact email: alan.oliveira.sa@gmail.com

Abstract

The use of communication networks to interconnect controllers and physical plants in industrial and critical infrastructure facilities exposes such control systems to threats typical of the cyber domain. In this sense, studies have been done to explore vulnerabilities and propose security solutions for Networked Control System (NCS). From the point of view of the control theory, the literature indicates that stealthy and accurate cyber-physical attacks must be planned based on an accurate knowledge about the model of the NCS. However, most literature about these attacks does not indicate how such knowledge is obtained by the attacker. So, to fill this hiatus, it is proposed and evaluated in this paper an Active System Identification attack, where the attacker injects data on the NCS to learn about its model. The attack is implemented based on two bio-inspired metaheuristics, namely: Backtracking Search Optimization Algorithm (BSA); and Particle Swarm Optimization (PSO). The results indicate a better performance of the BSA-based attack, especially when the captured signals contain white Gaussian noise. The goal of this paper is to demonstrate the degree of accuracy that this attack may achieve, highlighting the potential impacts and encouraging the research of possible countermeasures.