text: Intrusion Detection Systems (IDSs) are becoming essential to protecting modern information infrastructures. The effectiveness of an IDS is directly related to the computational resources at its disposal. However, it is difficult to guarantee especially with an increasing demand of network capacity and rapid proliferation of attacks. On the other hand, modern intrusions often come as sequences of attacks to reach some predefined goals. It is therefore critical to identify the best default IDS configuration to attain the highest possible overall protection within a given resource budget. This paper proposes a game theory based solution to the problem of optimal signature-based IDS configuration under resource constraints. We apply the concepts of indices of power, namely, Shapley value and Banzhaf-Coleman index, from cooperative game theory to quantify the influence or contribution of libraries in an IDS with respect to given attack graphs. Such valuations take into consideration the knowledge on common attack graphs and experienced system attacks and are used to configure an IDS optimally at its default state by solving a knapsack optimization problem.
  @cite_7: This talk will discuss issues and methods for survivability of systems under malicious attacks. To protect from such attacks, it is necessary to take steps to prevent attacks from succeeding. At the same time, it is important to recognize that not all attacks can be averted at the outset; attacks that are successful to some degree must be recognized as unavoidable and comprehensive support for identifying and responding to attacks is required.In my talk, I will describe the recent research on attack graphs that represent known attack sequences attackers can use to penetrate computer networks. I will show how attack graphs can be used to compute actual sets of hardening measures that guarantee the safety of given critical resources. Attack graphs can also be used to correlate received alerts, hypothesize missing alerts, and predict future alerts, all at the same time. Thus, they offer a promising solution for administrators to monitor and predict the progress of an intrusion, and take appropriate countermeasures in a timely manner.
  @cite_3: We present a method of analysis for evaluating intrusion detection systems. The method can be used to compare the performance of intrusion detectors, to evaluate performance goals for intrusion detectors, and to determine the best configuration of an intrusion detector for a given environment. The method uses a decision analysis that integrates and extends ROC (receiver operating characteristics) and cost analysis methods to provide an expected cost metric. We provide general results and illustrate the method in several numerical examples that cover a range of detectors that meet a performance goal and two actual detectors operating in a realistic environment. We demonstrate that, contrary to common advice, the value of an intrusion detection system and the optimal operation of that system depend not only on the system's ROC curve, but also on cost metrics and the hostility of the operating environment as summarized by the probability of intrusion. Extensions of the method are outlined, and conclusions are drawn.
summary: in @cite_3 use a decision analysis that integrates and extends Receiver Operating Characteristics (ROCs) to provide an expected cost metric. They demonstrate that the optimal operation point of an IDS depends not only on the system's own ROC curve and quantities such as the expected rate of false positives, false negatives, and the cost of operation, but also on the degree of hostility of an environment in which the IDS is situated, such as the probability and the type of an intrusion. Hence, the performance evaluation of an IDS has to take into account both the defender's side and attacker's side. In @cite_7 , a network security configuration problem is studied. A nonzero-sum stochastic game is formulated to capture the interactions among distributed intrusion detection systems in the network as well as their interactions against exogenous intruders. The authors have proposed the notion of security capacity as the largest achievable payoff to an agent at an equilibrium to yield performance limits on the network security, and a mathematical programming approach is used to characterize the equilibrium as well as the feasibility of a given security target.