Optimizing security patrolling scheduling in chemical industrial parks by using game theory

Protecting chemical clusters from intentional attacks has been a hot topic during the last decade. Besides intrusion security countermeasures such as cameras, entrances control etc., patrolling also fulfils an important role in the security of chemical facilities and industrial parks. Current patrolling strategies in industry are mainly single-plant driven and purely randomized or based on the patroller’s preference. Such an approach in a chemical industrial park is on the one hand not able to cover the more hazardous facilities more than the less hazardous plants within the park, and on the other hand is not able to deal with strategic (intelligent) human adversaries w.r.t. terrorism. This paper therefore investigates a game theoretic model for optimizing the schedule of patrolling in chemical clusters. The industrial defender and the intelligent/adaptive attackers are modelled as two players in the game. The defender aims at increasing the probability of detecting the attacker, by randomly but strategically scheduling her patrolling route. The attacker aims at causing maximal consequences with highest success probabilities, by choosing a proper attack time and a proper target. The model is further illustrated by a case study.