Critical infrastructure systems are complex networks of adaptive sociotechnical systems that provide the most fundamental requirements of the society. Their importance in the smooth conduct of the society has made their role more and more prominent. A failure in any of these important components of today's industrial society can well affect the lives of millions of people. It is not only their individual break down that raises serious concerns, but their mutual reliance (interdependency) is even more threatening. Although interdependency in these infrastructure systems provides many benefits for their operation, a failure in one can ripple down to the others and cause a catastrophic irremunerable event. In this paper, we have introduced a simulation suite for analyzing the behavior of interdependent critical infrastructure systems. The simulation suite focuses on the types of services that are provided by infrastructure components. Each infrastructure system component is modeled as an agent and its services as its behavior. We believe that this simulation suite can assist researchers in better understanding critical infrastructure behavior and hence prevent catastrophic failures.

The problem of spam detection is a crucial task in the web information retrieval systems. The dynamic nature of information resources as well as the continuous changes in the information demands of the users makes the task of web spam detection a challenging topic. So far many different methods from researchers with different backgrounds have been proposed to tackle with spam web pages problem. In this research, we study feature space of web spam detection to recognize most effective and discriminative features. Thereafter, we design a spam detection system that employs a minimum set of features and at the same time its performance is the same or very close to a system with the complete feature set. The experimental results show that we can reduce the number of features in a clever way while the accuracy of the system is intact or even improved.

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