Identifying Vulnerabilities of Industrial Control Systems using Evolutionary Multiobjective Optimisation

27 May 2020Nilufer TuptukStephen Hailes

In this paper we propose a novel methodology to assist in identifying vulnerabilities in a real-world complex heterogeneous industrial control systems (ICS) using two evolutionary multiobjective optimisation (EMO) algorithms, NSGA-II and SPEA2. Our approach is evaluated on a well known benchmark chemical plant simulator, the Tennessee Eastman (TE) process model... (read more)

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