Laobing Zhang

A Game‐Theoretical Model to Improve Process Plant Protection from Terrorist Attacks

The New York City 9/11 terrorist attacks urged people from academia as well as from industry to pay more attention to operational security research. The required focus in this type of research is human intention. Unlike safety-related accidents, security-related accidents have a deliberate nature, and one has to face intelligent adversaries with characteristics that traditional probabilistic risk assessment techniques are not capable of dealing with. In recent years, the mathematical tool of game theory, being capable to handle intelligent players, has been used in a variety of ways in terrorism risk assessment. In this article, we analyze the general intrusion detection system in process plants, and propose a game-theoretical model for security management in such plants. Players in our model are assumed to be rational and they play the game with complete information. Both the pure strategy and the mixed strategy solutions are explored and explained. We illustrate our model by an illustrative case, and find that in our case, no pure strategy but, instead, a mixed strategy Nash equilibrium exists.

Playing Chemical Plant Environmental Protection Games with Historical Monitoring Data

The chemical industry is very important for the world economy and this industrial sector represents a substantial income source for developing countries. However, existing regulations on controlling atmospheric pollutants, and the enforcement of these regulations, often are insufficient in such countries. As a result, the deterioration of surrounding ecosystems and a quality decrease of the atmospheric environment can be observed. Previous works in this domain fail to generate executable and pragmatic solutions for inspection agencies due to practical challenges. In addressing these challenges, we introduce a so-called Chemical Plant Environment Protection Game (CPEP) to generate reasonable schedules of high-accuracy air quality monitoring stations (i.e., daily management plans) for inspection agencies. First, so-called Stackelberg Security Games (SSGs) in conjunction with source estimation methods are applied into this research. Second, high-accuracy air quality monitoring stations as well as gas sensor modules are modeled in the CPEP game. Third, simplified data analysis on the regularly discharging of chemical plants is utilized to construct the CPEP game. Finally, an illustrative case study is used to investigate the effectiveness of the CPEP game, and a realistic case study is conducted to illustrate how the models and algorithms being proposed in this paper, work in daily practice. Results show that playing a CPEP game can reduce operational costs of high-accuracy air quality monitoring stations. Moreover, evidence suggests that playing the game leads to more compliance from the chemical plants towards the inspection agencies. Therefore, the CPEP game is able to assist the environmental protection authorities in daily management work and reduce the potential risks of gaseous pollutants dispersion incidents.

DAMS: A Model to Assess Domino Effects by Using Agent-Based Modeling and Simulation: Domino Effect Assessment by DAMS Model

Historical data analysis shows that escalation accidents, so-called domino effects, have an important role in disastrous accidents in the chemical and process industries. In this study, an agent-based modeling and simulation approach is proposed to study the propagation of domino effects in the chemical and process industries. Different from the analytical or Monte Carlo simulation approaches, which normally study the domino effect at probabilistic network levels, the agent-based modeling technique explains the domino effects from a bottom-up perspective. In this approach, the installations involved in a domino effect are modeled as agents whereas the interactions among the installations (e.g., by means of heat radiation) are modeled via the basic rules of the agents. Application of the developed model to several case studies demonstrates the ability of the model not only in modeling higher-level domino effects and synergistic effects but also in accounting for temporal dependencies. The model can readily be applied to large-scale complicated cases.

Protecting Process Industries from Intentional Attacks: The State of the Art

Large inventories of hazardous chemicals which can cause catastrophic consequences if released maliciously, the presence of chemical agents which can be stolen and be used either in later terrorist attacks or in making chemical and biochemical weapons, along with the key role of chemical plants in the economy and the public welfare and as an integral element in the supply chain have made the security of chemical plants a great concern especially since 9/11 terrorist attacks in the US. Aside from the importance of chemical plants themselves as potentially attractive targets to terrorist attacks, the usage of chemicals in more than half of the terrorist attacks worldwide further emphasizes the security assessment and management of chemical plants.

Single Plant Protection: Playing the Chemical Plant Protection Game Involving Attackers with Bounded Rationality

In this chapter, we model attackers with bounded rationality in the Chemical Plant Protection game. Three different behaviour models of attackers are investigated, namely, the epsilon-optimal attacker, the monotonic-optimal attacker, and the MiniMax attacker. All these attacker models are integrated to the Stackelberg CPP game, which means that the defender moves first, and the attackers follow. Furthermore, the monotonic-optimal attacker is investigated in the Interval CPP game with only one type of attacker, and a game solution named Monotoic MaxiMin Solution for the Interval CPP game (MoSICP) is defined [1]. The MoSICP solution incorporates both bounded rational attackers and distribution-free uncertainties into the CPP game. The epsilon-optimal attacker model, being related to the defender’s distribution-free uncertainties, and the MiniMax attacker model, being the most conservative model, are therefore investigated in the Bayesian Stackelberg CPP game framework, instead of in the Interval CPP game framework. The defender is still assumed to behave rationally to maximize her payoff.

Single Plant Protection: A Game-Theoretical Model for Improving Chemical Plant Protection

In this chapter, we introduce a game theoretic model for protecting a chemical plant from intelligent attackers. The model is named Chemical Plant Protection Game, abbreviated as “CPP Game” [1]. The CPP Game is developed based on the general intrusion detection approach in chemical plants. To this end, the general intrusion detection approach is firstly introduced. We develop and explain the CPP Game by modelling its players, strategies, and payoffs. Afterwards in Sect. 3.3, different equilibrium concepts are used to predict the outcome of the CPP Game [2]. An analysis of the inputs and outputs of the game is provided in Sect. 3.4, from an industrial practice point of view [3]. Finally, conclusions are drawn at the end of this chapter.

Single Plant Protection: Playing the Chemical Plant Protection Game with Distribution-Free Uncertainties

In this chapter, the Chemical Plant Protection game is extended to deal with input parameters with distribution-free uncertainties [1] The so-called interval CPP game is defined. Two algorithms, namely, the interval bi-matrix game solver (IBGS) and the interval CPP game solver (ICGS), are proposed.

Intelligent Interaction Modelling: Game Theory

Game theory is a mathematical tool for supporting decision making in a multiple players situation where one player’s utility will be determined not only by his own decision, but also by other players’ decisions. An illustrative example of this situation is the Rock/Scissors/Paper game (“RSP” game). In an RSP game, whether a player wins or loses depends on both what he plays and what his opponent plays. This is a well-known game between mostly children with very simple rules. Two ‘players’ hold their right hands out simultaneously at an agree signal to represent a rock (closed fist), a piece of paper (open palm), or a pair of scissors (first and second fingers held apart). If the two symbols are the same, it’s a draw. Otherwise rock blunts scissors, paper wraps rock, and scissors cut paper, so the respective winners for these three outcomes are rock, paper and scissors. The RSP game is what is called a ‘two-player zero-sum non-cooperative’ game. There are obviously many other types of game and the field of game theory is very powerful to provide (mathematical) insights into strategic decision-making.

Multi-plant Protection: A Game-Theoretical Model for Improving Chemical Clusters Patrolling

Due to economies of scale and all kinds of collaboration benefits, chemical plants are usually geographically clustered, forming chemical industrial parks or so-called ‘chemical clusters’. Some examples of such clusters are the Antwerp port chemical cluster in Belgium, the Rotterdam port chemical cluster in the Netherlands, the Houston chemical cluster in the US, or the Tianjin chemical cluster in China. Besides fixed security countermeasures within every plant, the patrolling of security guards is also scheduled, for securing these chemical facilities at different points and times, e.g. at night. The patrolling can either be single-plant oriented, which can be completely scheduled by the plant itself, or it can be multiple-plants oriented, which should be scheduled by an institute at a higher level than the single-plant level, for instance a multiple plant council (MPC) [1] Both types of patrolling have a drawback of not being able to deal with intelligent attackers. Some patrollers follow a fixed patrolling route, and in this case the adversary is able to predict the patroller’s position at a certain time. Other patrollers purely randomize their patrolling, without taking into consideration the hazardousness level that each installation/facility/plant holds, and if this is the case, the adversary may focus to attack the most dangerous installations/facilities/plants since all installations/facilities/plants are equally patrolled.