Network Security and Contagion

We develop a theoretical model of security investments in a network of interconnected agents. Network connections introduce the possibility of cascading failures due to an exogenous or endogenous attack depending on the profile of security investments by the agents. The general presumption in the literature, based on intuitive arguments or analysis of symmetric networks, is that because security investments create positive externalities on other agents, there will be underinvestment in security. We show that this reasoning is incomplete because of a first-order economic force: security investments are also strategic substitutes. In a general (non-symmetric) network, this implies that underinvestment by some agents will encourage overinvestment by others. We demonstrate by means of examples there can be overinvestment by some agents and also that aggregate probabilities of infection can be lower in equilibrium compared to the social optimum. We then provide sufficient conditions for underinvestment. This requires both sufficiently convex cost functions (convexity alone is not enough) and networks that are either symmetric or locally tree-like. We also characterize the impact of network structure on equilibrium and optimal investments. Finally, we show that when the attack location is endogenized (by assuming that the attacker chooses a probability distribution over the location of the attack in order to maximize damage), there is an additional incentive for overinvestment: greater investment by an agent shifts the attack to other parts of the network.We thank various numerous seminar and conference participants for useful suggestions. We gratefully acknowledge financial support from the Toulouse Network with Information Technology and Army Research Office

Avoiding Interruptions - QoE Trade-offs in Block-coded Streaming Media Applications

We take an analytical approach to study Quality of user Experience (QoE) for video streaming applications. First, we show that random linear network coding applied to blocks of video frames can significantly simplify the packet requests at the network layer and save resources by avoiding duplicate packet reception. Network coding allows us to model the receiver's buffer as a queue with Poisson arrivals and deterministic departures. We consider the probability of interruption in video playback as well as the number of initially buffered packets (initial waiting time) as the QoE metrics. We characterize the optimal trade-off between these metrics by providing upper and lower bounds on the minimum initial buffer size, required to achieve certain level of interruption probability for different regimes of the system parameters. Our bounds are asymptotically tight as the file size goes to infinity.Comment: Submitted to ISIT 2010 - Full versio

When is Society Susceptible to Manipulation?

We consider a social learning model where agents learn about an underlying state of the world from individual observations as well as from exchanging information with each other. A principal (e.g. a firm or a government) interferes with the learning process in order to manipulate the beliefs of the agents. By utilizing the same forces that give rise to the ``wisdom of the crowd'' phenomenon, the principal can get the agents to take an action that is not necessarily optimal for them but is in the principal's best interest. We characterize which networks are susceptible to this kind of manipulation and derive conditions under which a social network is impervious and cannot be manipulated. In the process, we generalize some known centrality measures and describe how our model offers insights into designing networks that are resistant to manipulation.https://deepblue.lib.umich.edu/bitstream/2027.42/154046/1/reputation-v11Submit.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/154046/4/manipulation.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/154046/5/manipulation-final.pd

The Network Origins of Large Economic Downturns

This paper shows that large economic downturns may result from the propagation of microeconomic shocks over the input-output linkages across different firms or sectors within the economy. Building on the framework of Acemoglu et al. (2012), we argue that the economy’s input-output structure can fundamentally reshape the distribution of aggregate output, increasing the likelihood of large downturns from infinitesimal to substantial. More specifically, we show that an economy with non-trivial intersectoral input-output linkages that is subject to thin-tailed productivity shocks may exhibit deep recessions as frequently as economies that are subject to heavy-tailed shocks. Moreover, we show that in the presence of input-output linkages, aggregate volatility is not necessarily a sufficient statistic for the likelihood of large downturns. Rather, depending on the shape of the distribution of the idiosyncratic shocks, different features of the economy’s input-output network may be of first-order importance. Finally, our results establish that the effects of the economy’s input-output structure and the nature of the idiosyncratic firm level shocks on aggregate output are not separable, in the sense that the likelihood of large economic downturns is determined by the interplay between the two

Game Theory and Mechanism Design

This course is offered to graduates and is an introduction to fundamentals of game theory and mechanism design with motivations drawn from various applications including distributed control of wireline and wireless communication networks, incentive-compatible/dynamic resource allocation, and pricing. Emphasis is placed on the foundations of the theory, mathematical tools, as well as modeling and the equilibrium notions in different environments. Topics covered include: normal form games, learning in games, supermodular games, potential games, dynamic games, subgame perfect equilibrium, bargaining, repeated games, auctions, mechanism design, cooperative game theory, network and congestion games, and price of anarchy