  Cybersecurity of industrial control system is a very complex and challenging
research topic, due to the integration of these systems in national critical
infrastructures. The control systems are now interconnected in industrial
networks and frequently to the Internet. In this context they are becoming
targets of various cyber attacks conducted by malicious people such as hackers,
script kiddies, industrial spies and even foreign armies and intelligence
agencies. In this paper the authors propose a way to model the most frequent
attacker profiles and to estimate the success rate of an attack conducted in
given conditions. The authors use a fuzzy approach for generating attacker
profiles based on attacker attributes such as knowledge, technical resources
and motivation. The attack success rate is obtained by using another fuzzy
inference system that analyzes the attacker profile and system intrinsic
characteristics.
