This paper considers a friendly interferer allocating jamming power to eavesdropping channels to increase the level of secrecy of a wireless network. The friendly interferer has access to limited power, while the eavesdropper may not have the ability to attack all channels simultaneously. When all channels used for secret communication are under the threat of eavesdropping attacks, the optimal power allocation policy results from solving a convex optimization problem. In this case, the optimal policy is unique and can be obtained via a water-filling scheme. When the eavesdropper can not attack all channels, the eavesdropper should behave strategically and may select targets probabilistically. We propose a non-zero-sum game that helps the friendly interferer predict and concentrate on the targets selected by the eavesdropper. Under certain conditions, we prove that there exists a unique Nash equilibrium (NE) strategy pair, which has a threshold type structure. We provide conditions under which the eavesdropper’s equilibrium strategy is deterministic. We devise a strategy iteration algorithm to compute an equilibrium power allocation strategy. We present examples showing that the game-theoretic power allocation strategy performs better than the conservative power allocation strategy that assumes every channel to be under attack.

We present a novel analytical model to approximate the travel-time distribution of vehicles traversing a freeway corridor that experiences random quality of service degradations due to non-recurrent incidents. The proposed model derives the generating function of travel times in closed-form using clearance time, incident frequency and severity, and other ordinary traffic characteristics. We validate the model using data from a freeway corridor where weather events and traffic accidents serve as the principal causes of service degradation. The resulting model is equivalent in performance to widely used methodologies while uniquely providing a clear connection on how incidents affect travel time distribution. With this connection, the model readily yields travel time reliability measures for alternative roadway behaviors, providing crucial information for long-term planning.

This paper considers network protection games against different types of attackers for a heterogeneous network system with N units. A defender, by applying resources to networked units, can decrease the units’ vulnerabilities. At the same time, the defender needs to take into account the cost of using defense resources. Two non-zero sum Nash games against two different types of attackers are studied. The first type tries to maximize damage based on the value of security assets related to networked units, while the second type aims at infiltrating the network. The analyses show that there exists a cut-off index determining the set of units that will be protected in the equilibrium strategies of the first game, while either all units or none will be covered in the equilibria of the second game. An application of the network protection game to secure wireless communication networks is presented.

The security community has witnessed a significant increase in the number of different types of security threats. This situation calls for the design of new techniques that can be incorporated into security protocols to meet these challenges successfully. An important tool for developing new security protocols as well as estimating their effectiveness is game theory. This game theory framework usually involves two players or agents: 1) a protector and 2) an adversary, and two patterns of agent behavior are considered: 1) selfish behavior, where each of the agents wants to maximize his payoff; and 2) leader and follower behavior, where one agent (the leader) expects that the other agent (the follower) will respond to the leader's strategy. Such an approach assumes that the agents agree on which strategy to apply in advance. In this paper, this strong assumption is relaxed. Namely, the following question is considered: what happens if it is unknown a priori what pattern of behavior the adversary is going to use, or in other words, it is not known, what game he intends to play? Using a simple game-theoretic model, it is shown that the protector can lose if he does not take into account the possibility that the adversary can play a game other than the one the protector has in mind. Further considered is a repeated game in which the protector can learn about the presence of an adversary, and the behavior of belief probabilities is analyzed in this setting.

Secret and reliable communication presents a challenge involving a double dilemma for a user and an adversary. One challenge for the adversary is to decide between jamming and eavesdropping. While jamming can be quite effective in preventing reliable communication of the user, it can also be quite harmful for the adversary since he/she can be detected. On the other hand, eavesdropping is quite safe for the adversary; however, it sometimes may not be so efficient compared to jamming, if the adversary cannot respond to the information gleaned from eavesdropping in a timely manner. The user can either transmit, thus becoming vulnerable to malicious activity, or be in a silent mode in turn delaying his/her transmission. However, by combining these modes properly the user can assist an intruder detection system in detecting the adversary, since transmission can provoke the adversary into a jamming attack, and a strategically allocated silent mode while the jammer continues jamming can increase the probability of detecting the adversary. In this paper, to get insight into this problem, two simple stochastic games are proposed. Explicit solutions are found that lead to the characterization of some interesting properties. In particular, it is shown that under certain conditions, incorporating in the transmission protocol a time slot dealing just with the detection of malicious threats can improve the secrecy and reliability of the communication without extra transmission delay.

Network security against possible attacks involves making decisions under uncertainty. Not only may one be ignorant of the place, the power, or the time of potential attacks, one may also be largely ignorant of the attacker's purpose. To illustrate this phenomenon, this paper proposes a simple Bayesian game-theoretic model of allocating defensive (scanning) effort among nodes of a network in which a network's defender does not know the adversary's motivation for intruding on the network, e.g., to bring the maximal damage to the network (for example, to steal credit card numbers or information on bank accounts stored there) or to infiltrate the network for other purposes (for example, to corrupt nodes for a further distributed denial of service botnet attack on servers). Due to limited defensive capabilities, the defender faces the dilemma of either: 1) focusing on increasing defense of the most valuable nodes, and in turn, increasing the chance for the adversary to sneak into the network through less valuable nodes or 2) taking care of defense of all the nodes, and in turn, reducing the level of defense of the most valuable ones. An explicit solution to this dilemma is suggested based on the information available to the defender, and it is shown how this information allows the authorities to increase the efficiency of a network's defense. Some interesting properties of the rivals' strategies are presented. Notably, the adversary's strategy has a node-sharing structure and the adversary's payoffs have a discontinuous dependence on the probability of the attack's type. This discontinuity implies that the defender has to take into account the human factor since some threshold values of this inclination in the adversary's behavior could make the defender's policy very sensitive to small perturbations, while in other situations it produces minimal impact.

We study a Petri net model of a system composed of two processes sharing a resource. Conflicts may occur over the usage of the shared resource, thus making the system nondeterministic. Therefore, in the context of minimax algebra, it cannot be formulated as a linear system in order to compute its performance measures. However, if the sequence by which the resource is allocated to the two processes is known, we can transform the system into a decision-free net. For this system with an imposed constraint on the resource allocation frequencies, we show that the optimal allocation sequence is the most regular integer sequence satisfying that constraint. We also discuss the periodic behavior of this system under no constraints on the resource allocation frequencies.>

The authors describe a multilayer connection control architecture for broadband communications. A graph framework is introduced to describe network layers of network design, path configurations, dynamic call routing, burst switching, and asynchronous transfer mode (ATM) cell switching. These hierarchical layers of switching are performed at decreasing time scales, respectively. Switching at the higher layer is performed to reduce blocking at the next smaller time scale. A layered notion of equivalent bandwidth for satisfying layered grade-of-service parameters is introduced for making connections at these time scales. The authors then focus on the path configuration layer. Two path setup methods, namely, physical and virtual path setup, are described. Mathematical programs minimizing path bandwidth usage subject to meeting grade-of-service requirements are formulated for both methods. The relative merits of these methods are compared. In one example, physical path setup is shown to require roughly 50% more bandwidth than virtual path setup.>