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The Resource Decision and Game Theory for Security : 4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings

Decision and Game Theory for Security : 4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings

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Decision and Game Theory for Security : 4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings
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Decision and Game Theory for Security
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4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings
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eng
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MiAaPQ
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non fiction
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dictionaries
Decision and Game Theory for Security : 4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings
Label
Decision and Game Theory for Security : 4th International Conference, GameSec 2013, Fort Worth, TX, USA, November 11-12, 2013. Proceedings
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http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=3101143
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface -- Organization -- Table of Contents -- On Communication over Gaussian Sensor Networks with Adversaries: Further Results -- 1 Introduction -- 2 Problem Definition -- 3 Review of Prior Work -- 3.1 Full Coordination -- 3.2 No Coordination -- 4 MainResult -- 5 Conclusion -- References -- A True Random Generator Using Human Gameplay -- 1 Introduction -- 1.1 Our Contribution -- 1.2 Related Work -- 2 Preliminaries -- 2.1 Expander Graphs -- 2.2 A Simple Explicit Construction for Expander Graphs -- 2.3 Game Theoretic Definitions -- 3 TRG Using Human Input in Games -- 4 Experiments -- 4.1 The Game -- 4.2 Measuring Min-Entropy -- 4.3 Measuring Statistical Property of a Source -- 4.4 Measures of Randomness for Our Game -- 5 Concluding Remarks -- References -- A Game Theoretic Analysis of Collaboration in Wikipedia -- 1 Introduction -- 2 User Contribution as a Non-cooperative Game -- 3 Empirical Validation with Data -- 3.1 Extracting Data from Wikipedia Articles -- 3.2 Numerical Verification of the Analysis -- 4 Trustworthy Collaboration and Vandalism -- 5 Conclusion -- References -- Controllability of Dynamical Systems: Threat Models and Reactive Security -- 1 Introduction -- 2 SystemModel -- 3 Control/Security Properties -- 4 Attack Model -- 4.1 Goals of an Attacker -- 4.2 Offline Information Available to the Attacker -- 4.3 Online Information (and Access) Available to the Attacker -- 5 Attacking Controllability -- 5.1 Attacking Controllability with u(t) -- 5.2 Attacking Controllability with y(t) -- 6 Reactive Security: Differential Games -- 6.1 Threat Model and Differential Games Solutions -- 7 Differential Game Example -- 7.1 Simulation Results -- 8 Heuristic Stability Game -- 8.1 Linearization and Control Design -- 8.2 Attacker Perspective -- 8.3 System Defense -- 8.4 Simulations -- 9 Future Work -- References
  • Adaptive Regret Minimization in Bounded-Memory Games -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 Definition of Regret -- 4.1 AdversaryModel -- 4.2 k-adaptive Regret -- 5 Audit Examples -- 6 Hardness Results -- 7 Regret Minimization Algorithms -- 7.1 Reduction to Repeated Games -- 7.2 Efficient Approximate RegretMinimization Algorithms -- 8 Open Questions -- References -- The Cooperative Ballistic Missile Defence Game -- 1 Introduction -- 2 The Optimization Phase -- 2.1 Problem Setting -- 2.2 Formal Description -- 2.3 The Cost Function and Constraints -- 2.4 Computing the Optimal Assignment -- 3 The Cooperative Phase -- 3.1 The Interceptor Savings Game -- 3.2 Allocating the Savings -- 3.3 Big Boss Game -- 4 Conclusions -- References -- Security Games for Virtual Machine Allocation in Cloud Computing -- 1 Introduction -- 2 Background and Problem Statement -- 2.1 Methods to Achieve Co-residence -- 2.2 Potential Security Risks -- 2.3 Possible Countermeasures -- 2.4 Problem Statement -- 3 Proposed Game Model -- 3.1 Attack Scenarios and Metrics -- 3.2 Defence Policies -- 3.3 Game Model -- 4 Analysis of VM Allocation Policies Using the Game Model -- 4.1 Simulation Environment -- 4.2 Attack Efficiency under Different VM Allocation Policies -- 4.3 Coverage Rate under Different VM Allocation Policies -- 4.4 Power Consumption under Different VM Allocation Policies -- 4.5 Workload Balance under Different VM Allocation Policies -- 4.6 Other Criteria -- 4.7 Numerical Solutions and Discussion -- 5 Conclusion and Future Work -- References -- Monotonic Maximin: A Robust Stackelberg Solution against Boundedly Rational Followers -- 1 Introduction -- 1.1 RelatedWork -- 2 Preliminaries -- 3 Monotonic Maximin -- 3.1 Existence of Monotonic Maximin Solutions -- 3.2 Optimality against Interiority, Continuity and Responsiveness
  • 3.3 Capturing Other Behavioral and UncertaintyModels -- 3.4 Top-MonotonicMaximin -- 4 Computation of Monotonic Maximin -- 4.1 Multiple-LP Formulation -- 4.2 MILP Formulation -- 4.3 Computing Top-Monotonic Maximin -- 5 Structure of Monotonic Maximin Solutions -- 5.1 Extreme Points of the Set of Monotonic Follower Strategies -- 5.2 Proof of Proposition 5 -- 6 Evaluation -- 6.1 Payoff Structures -- 6.2 Solution Quality againstWorst-CaseMonotonic Attackers -- 6.3 Solution Quality against Non-monotonic Attackers -- 6.4 Runtime Performance -- 7 Conclusion and Future Work -- References -- Defeating Tyranny of the Masses in Crowdsourcing: Accounting for Low-Skilled and Adversarial Workers -- 1 Introduction -- 2 Modeling Paradigm -- 3 Framework -- 3.1 Notation -- 3.2 Stochastic Generation Model -- 3.3 Worker Types -- 3.4 Incomplete, Complete and Expected Complete Data Log Likelihood -- 4 The Generalized EM (GEM) Algorithm -- 4.1 Unsupervised GEM -- 5 Experiments -- 5.1 Experiments with Synthetic Data -- 5.2 Simulating a Crowd Using an Ensemble of Classifiers -- 5.3 MTurk Experiment -- 6 Related Work -- 7 Conclusion -- References -- Quantifying Network Topology Robustness under Budget Constraints: General Model and Computational Complexity -- 1 Introduction -- 2 Unconstrained Network Blocking Games -- 2.1 Communication Models -- 2.2 Game-Theoretic Measure of Robustness -- 2.3 Equilibrium Characterization Based on Blocking Pairs of Polyhedra -- 3 Computational Complexity of the Unconstrained Game -- 4 Budget Contraints -- 4.1 Unit Usage / Protection Cost -- 4.2 Maximum Cost Budget Constraint -- 4.3 Expected Cost Budget Constraint -- 4.4 Constrained Game -- 5 NP-Hardness of the Maximum Cost Constraint -- 6 Efficient Algorithms for the Expected Cost Constraint -- 7 Application Example: Vulnerability/Budget Tradeoff -- 8 Conclusions and Future Work -- References
  • Mitigation of Targeted and Non-targeted Covert Attacks as a Timing Game -- 1 Introduction -- 2 Related Work -- 2.1 Games of Timing -- 2.2 FlipIt: Modeling Targeted Attacks -- 3 Model Definition -- 3.1 Types of Strategies for the Defender and the Targeted Attacker -- 3.2 Non-targeted Attacks -- 3.3 Comparison to FlipIt -- 4 Analytical Results -- 4.1 Nash Equilibrium for Targeted Attacker and Renewal Defender -- 4.2 Equilibrium for Both Targeted and Non-targeted Attackers -- 5 Numerical Illustrations -- 6 Conclusions -- References -- New Efficient Utility Upper Bounds for the Fully Adaptive Model of Attack Trees -- 1 Introduction -- 2 Definitions and Related Work -- 2.1 Definitions -- 2.2 Related Work -- 3 TheNewModel -- 3.1 Precise Utility Computation -- 3.2 Utility Upper Bound Estimation Using Utility Propagation -- 4 Computational Complexity of the New Model -- 5 Efficient Computation of Expenses Lower Bounds -- 5.1 Expenses Propagation -- 5.2 Expenses Reduction -- 6 Interpretation of Results -- 7 Open Questions and Future Research -- References -- Optimizing Active Cyber Defense -- 1 Introduction -- 1.1 Our Contributions -- 2 Related Work -- 3 The Basic Active Cyber Defense Model -- 4 Optimal Control for Strategic Defender against Non-strategic Attacker -- 4.1 Infinite-Time Horizon Optimal Control -- 4.2 Fast Optimal Control for Strategic Defenders against Non-strategic Attackers -- 5 Nash Equilibria for Strategic Attacker and Defender -- 6 Conclusion -- References -- Equilibrium Concepts for Rational Multiparty Computation -- 1 Introduction -- 2 Related Work -- 3 Motivation -- 4 Equilibrium Concepts -- 4.1 Normal Form Games -- 4.2 Extensive Form Games -- 5 Framework -- 5.1 Privacy -- 5.2 Correctness -- 5.3 Fairness -- 6 Conclusion -- References -- Game-Theoretic Approach to Feedback-Driven Multi-stage Moving Target Defense -- 1 Introduction
  • 2 Related Work -- 3 System Model -- 4 Moving Target Defense -- 5 Learning Dynamics -- 6 Numerical Example -- 7 Conclusions -- References -- Author Index
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9783319027869
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computer
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rdamedia
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