Spam-based advertising is a business. While it has engendered both widespread antipathy and a multi-billion dollar anti-spam industry, it continues to exist because it fuels a profitable enterprise. We lack, however, a solid understanding of this enterprise's full structure, and thus most anti-Spam interventions focus on only one facet of the overall spam value chain (e.g., spam filtering, URL blacklisting, site takedown).In this paper we present a holistic analysis that quantifies the full set of resources employed to monetize spam email -- including naming, hosting, payment and fulfillment -- using extensive measurements of three months of diverse spam data, broad crawling of naming and hosting infrastructures, and over 100 purchases from spam-advertised sites. We relate these resources to the organizations who administer them and then use this data to characterize the relative prospects for defensive interventions at each link in the spam value chain. In particular, we provide the first strong evidence of payment bottlenecks in the spam value chain, 95% of spam-advertised pharmaceutical, replica and software products are monetized using merchant services from just a handful of banks.

In this paper, we study the problem of efficient medium access control (MAC) among cognitive radio devices that are equipped with multiple radios and thus are capable of transmitting simultaneously at different frequencies (channels). We assume that radios contend on each channel using the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. We study two MAC problems: (i) the allocation of the available channels among radios, and (ii) the optimal usage of each allocated channel by the radios occupying it. Both problems are studied in a game-theoretic setting, where devices aim to selfishly maximize their share of the available bandwidth. As for the first problem, we show that the “price of anarchy” is close to 1, that is, Nash equilibria imply nearly system optimal allocations of the available channels. For the second problem, we design a game such that it admits a unique Nash equilibrium that is is both fair and Pareto-optimal. Furthermore, we propose simple mechanisms that enable selfish cognitive radio devices not only to coordinate efficiently on the available channels but also to optimally use every single allocated channel.

A frequently proposed solution to node misbehavior in mobile ad hoc networks is to use reputation systems. But in ephemeral networks - a new breed of mobile networks where contact times between nodes are short and neighbors change frequently - reputations are hard to build. In this case, local revocation is a faster and more efficient alternative. In this paper, we define a game-theoretic model to analyze the various local revocation strategies. We establish and prove the conditions leading to subgame-perfect equilibria. We also derive the optimal parameters for voting-based schemes. Then we design a protocol based on our analysis and the practical aspects that cannot be captured in the model. With realistic simulations on ephemeral networks we compare the performance and economic costs of the different techniques.

Wireless social community networks are emerging as a new alternative to providing wireless data access in urban areas. By relying on users in the network deployment, a wireless community can rapidly deploy a high-quality data access infrastructure in an inexpensive way. But, the coverage of such a network is limited by the set of access points deployed by the users. Currently, it is not clear if this paradigm can serve as a replacement of existing centralized networks operating in licensed bands (such as cellular networks) or if it should be considered as a complimentary service only, with limited coverage. This question currently concerns many wireless network operators. In this paper, we study the dynamics of wireless social community networks by using a simple analytical model. In this model, users choose their service provider based on the subscription fee and the offered coverage. We show how the evolution of social community networks depends on their initial coverage, the subscription fee, and the user preferences for coverage. We conclude that by using an efficient static or dynamic pricing strategy, the wireless social community can obtain a high coverage. Using a game-theoretic approach, we then study a case where the mobile users can choose between the services provided by a licensed band operator and those of a social community. We show that for specific distribution of user preferences, there exists a Nash equilibrium for this non-cooperative game.

Channel allocation was extensively studied in the framework of cellular networks. But the emergence of new system concepts, such as cognitive radio systems, has brought this topic into the focus of research again. In this paper, we study in detail the problem of competitive multi-radio multi-channel allocation in wireless networks. We study the existence of Nash equilibria in a static game and we conclude that, in spite of the non-cooperative behavior of such devices, their channel allocation results in a load-balancing solution. In addition, we consider the fairness properties of the resulting channel allocations and their resistance to the possible coalitions of a subset of players. Finally, we present three algorithms that achieve a load-balancing Nash equilibrium channel allocation; each of them using a different set of available information.

In each country today, cellular networks operate on carefully separated frequency bands. This separation is imposed by the regulators of the given country to avoid interference between these networks. But, the separation is only valid within the borders of a country, hence the operators are left on their own to resolve cross-border interference of their cellular networks. In this paper, we focus on the scenario of two operators, each located on one side of the border. We assume that they want to fine-tune the emitting power of the pilot signals (i.e., beacon signals) of their base stations. This operation is crucial, because the pilot signal power determines the number of users they can attract and hence the revenue they can obtain. In the case of no power costs, we show that there exists a motivation for the operators to be strategic, meaning to fine-tune the pilot signal powers of their base stations. In addition, we study Nash equilibrium conditions in an empirical model and investigate the efficiency of the Nash equilibria for different user densities. Finally, we modify our game model to take power costs into account. The game with power costs corresponds to the well-known prisoner's dilemma: The players are still motivated to adjust their pilot powers, but their strategic behavior leads to a sub-optimal Nash equilibrium.

In this paper, we consider the application of delay-tolerant networks to personal wireless communications. In these networks, selfish nodes can exploit the services provided by other nodes by downloading messages that interest them, but refusing to store and distribute messages for the benefit of other nodes. We propose a mechanism to discourage selfish behavior based on the principles of barter. We develop a game-theoretic model in which we show that the proposed approach indeed stimulates cooperation of the nodes. In addition, the results show that the individually most beneficial behavior leads to the social optimum of the system.

So far, cellular networks have been operated in "private" frequency bands. But recently, several researchers and legislators have argued in favor of a more flexible and more efficient management of the spectrum, leading to the possible coexistence of several network operators in a shared frequency band. In this paper, we study this situation in detail, assuming that mobile devices can freely roam among the various operators. Free roaming means that the mobile devices measure the signal strength of the pilot signals (i.e., beacon signals) of the base stations and attach to the base station with the strongest pilot signal. We model the behavior of the network operators in a game theoretic setting in which each operator decides about the power of the pilot signal of its base stations. We first identify possible Nash equilibria in the theoretical setting in which all base stations are located on the vertices of a two-dimensional lattice. We then relax this topological assumption and show that, in the more general case, finding the Nash equilibria is an NP-complete problem. Finally, we prove that a socially optimal Nash equilibrium exists and that it can be enforced by using punishments.

In self-organizing ad hoc networks, all the networking functions rely on the contribution of the participants. As a basic example, nodes have to forward packets for each other in order to enable multihop communication. In recent years, incentive mechanisms have been proposed to give nodes incentive to cooperate, especially in packet forwarding. However, the need for these mechanisms was not formally justified. In this paper, we address the problem of whether cooperation can exist without incentive mechanisms. We propose a model,based on game theory and graph theory to investigate equilibrium conditions of packet forwarding strategies. We prove theorems about the equilibrium conditions for both cooperative and noncooperative strategies. We perform simulations to estimate the probability that the conditions for a cooperative equilibrium hold in randomly generated network scenarios.. As the problem is involved, we deliberately restrict ourselves to a static configuration. We conclude that in static ad hoc networks where the relationships between the nodes are likely to be stab le-cooperation needs to be encouraged.