We study the connectivity properties of the Internet graph and its impact on its structure.

The fundamental objective of sensor networks underpinning a variety of applications is the collection of reliable information from the surrounding environment. The correctness of the collected data is especially important in applications involving societal welfare and safety, in which the acquired information may be utilized by end-users for decision-making. The distributed nature of sensor networks and their deployment in unattended and potentially hostile environments, however, renders this collection task challenging for both scalar and visual data. In this work we propose and address the twin problem of carrying out and defending against a stealthy attack on the information gathered by a sensor network at the physical sensing layer as perpetrated by a competing hostile network. A stealthy attack in this context is an intelligent attempt to disinform a sensor network in a manner that mitigates attack discovery. In comparison with previous sensor network security studies, we explicitly model the attack scenario as an active competition between two networks where difficulties arise from the pervasive nature of the attack, the possibility of tampering during data acquisition prior to encryption, and the lack of prior knowledge regarding the characteristics of the attack. We examine the problem from the perspective of both the hostile and the legitimate network. The interaction between the networks is modeled as a game where a stealth utility is derived and shown to be consistent for both players in the case of stealthy direct attacks and stealthy cross attacks. Based on the stealth utility, the optimal attack and defense strategies are obtained for each network. For the legitimate network, minimization of the attacker’s stealth results in the possibility of attack detection through established paradigms and the ability to mitigate the power of the attack. For the hostile network, maximization of the stealth utility translates into the optimal attack avoidance. This attack avoidance does not require active communication among the hostile nodes but rather relies on a level of coordination which we quantify. We demonstrate the significance and effectiveness of the solution for sensor networks acquiring scalar and multidimensional data such as surveillance sequences and relate the results to existing image sensor networks. Finally we discuss the implications of these results for achieving secure event acquisition in unattended environments.

Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 15, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. X. H. Wang Vita. Includes bibliographical references.

 Surge in WLAN development leads to urgent demand for more efficient bandwidth allocation methods. The bandwidth resource becomes more and more scarce. As a consequence, it demands both revenue maximizing and cost efficient allocation methods. To develop this sort of allocation methods, a dilemma between the target of maximizing service quality (in terms of user revenue) and the target of cost efficient allocation must be resolved. In this thesis, two novel auction-based time-slotted WLAN bandwidth allocation models are established, namely the Combination of Single-slot Second-Price Sealed Auction (CSSA) and the Multi-slot Vickrey Auction versus Homogeneous Objects (MVAH). The two models propose a new approach to the solution of the dilemma: user revenue is formulated by not only its revenue gain or loss related to the access to the bandwidth resource, but also by a series of WLAN transmission factors, including Packet Collision Rate and Minimal Packet Transmission error rate. In the two models, wireless bandwidth is time-slotted and bandwidth users compete for the access to these time slots. Initially, each bandwidth user joins a bidding group which is represented by its bidder. There is only one bandwidth provider in the coverage area of the WLAN. After being assigned virtual credit budget, every bidder bids for arbitrary slot combination in each bidding trial or all slots in one bidding trial, according to the bidding rule of adopted allocation model. Non-cooperative game formulation is thereafter introduced to analyze the revenue of each bidder, revenue of the provider, and revenue of the whole allocation system. Specifically, each bidder’s revenue function is differentiated by its bid; the extreme points of this partial differential equation, i.e., the best bids for the bidder, are computed. The bidding strategy formula for each single bidder is derived from the game formulation under the bidder’s budget limit. Each bidder adjusts its bids to attain the optimal revenue obtained from the bidding strategy formula. The allocation pattern is therefore formed. By means of calculation of the all-bidder revenue to whole system revenue ratio, the system efficiency values for both allocation models are analyzed. Conclusions can be derived from the formula of system efficiency: 1) CSSA benefits about 1 percent higher system efficiency unit than MVAH when only average throughputs of user groups differ. And both models iii- gain optimal system efficiencies when bidder’s average throughput differs 65 times pairwise. 2) The larger the number of users connecting to each bidder, the lower the system efficiency. And CSSA model attains higher system efficiency than MVAH when user numbers of user groups differ more than 3.2 times pairwise. In accordance with the pursuit of maximum system efficiency, new WLANs satisfying both revenue maximizing and cost efficient allocation demands can be established. / published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

This dissertation focuses on strategic behavior and database privacy. First, we look at strategic behavior as a tool for distributed computation. We blend the perspectives of game theory and mechanism design in proposals for distributed solutions to the classical set cover optimization problem. We endow agents with natural individual incentives, and we show that centrally broadcasting non-binding advice effectively guides the system to a near-optimal state while keeping the original incentive structure intact. We next turn to the database privacy setting, in which an analyst wishes to learn something from a database, but the individuals contributing the data want to protect their personal information. The notion of differential privacy allows us to do both by obscuring true answers to statistical queries with a small amount of noise. The ability to conduct a task differentially privately depends on whether the amount of noise required for privacy still permits statistical accuracy. We show that it is possible to give a satisfying tradeoff between privacy and accuracy for a computational problem called independent component analysis (ICA), which seeks to decompose an observed signal into its underlying independent source variables. We do this by releasing a perturbation of a compact representation of the observed data. This approach allows us to preserve individual privacy while releasing information that can be used to reconstruct the underlying relationship between the observed variables. In almost all of the differential privacy literature, the privacy requirement must be specified before looking at the data, and the noise added for privacy limits the statistical utility of the sanitized data. The third part of this dissertation ties together privacy and strategic behavior to answer the question of how to determine an appropriate level of privacy when data contributors prefer more privacy but an analyst prefers more accuracy. The proposed solution to this problem views privacy as a public good and uses market design techniques to collect these preferences and then privately select and enforce a socially efficient level of privacy.

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The author suggests using lessons from Game Theory to improve the negotiation process and to construct more fitting agreements upon the breakdown of the family unit in the cases of separation or divorce. Currently many settlement agreements are inappropriate for the parties for a variety of reasons, including not establishing the parties' true interests during the negotiations. Furthermore, an inappropriate agreement may not be reopened by the court, given strict procedural and jurisprudential requirements. Game Theory lessons promote communication, cooperation, and forgiveness without allowing either party to be manipulated. These elements, already found in Collaborative Law, favour incorporating the lessons from Game Theory into this negotiation process.

This thesis contributes to a re-examination and extension of the equilibrium concept in normal and extensive form games. The equilibrium concept is a solution concept for games that is consistent with individual rationality and various assumptions about players' knowledge about the nature of their strategic interaction. The thesis argues that further consistency conditions can be imposed on a rational solution concept. By its very nature, a rational solution concept implicitly defines which strategies are non-rational. A rational player's beliefs about play by non-rational opponents should be consistent with this implicit definition of non-rational play. The thesis shows that equilibrium concepts that satisfy additional consistency requirements can be formulated in Choquet-expected utility theory, i.e. non-expected utility theory with non-additive or set-valued beliefs, together with an empirical assumption about players' attitude toward uncertainty. Chapter 1 introduces the background of this thesis. We present the conceptual problems in the foundations of game theory that motivate our approach. We then survey the decision-theoretic foundations of Choquet-expected utility theory and game-theoretic applications of Choquet-expected utility theory that are related to the present approach. Chapter 2 formulates this equilibrium concept for normal form games. This concept, called Choquet-Nash Equilibrium, is shown to be a generalization of Nash Equilibrium in normal form games. We establish an existence result for finite games, derive various properties of equilibria and establish robustness results for Nash equilibria. Chapter 3 extends the analysis to extensive games. We present the equivalent of subgame-perfect equilibrium, called perfect Choquet Equilibrium, for extensive games. Our main finding here is that perfect Choquet equilibrium does not generalize, but is qualitatively different from subgame-perfect equilibrium. Finally, in chapter 4 we examine the centipede game. It is shown that the plausible assumption of bounded uncertainty aversion leads to an 'interior' equilibrium of the centipede game.