Preface 1. Decision-Theoretic Foundations 1.1 Game Theory, Rationality, and Intelligence 1.2 Basic Concepts of Decision Theory 1.3 Axioms 1.4 The Expected-Utility Maximization Theorem 1.5 Equivalent Representations 1.6 Bayesian Conditional-Probability Systems 1.7 Limitations of the Bayesian Model 1.8 Domination 1.9 Proofs of the Domination Theorems Exercises 2. Basic Models 2.1 Games in Extensive Form 2.2 Strategic Form and the Normal Representation 2.3 Equivalence of Strategic-Form Games 2.4 Reduced Normal Representations 2.5 Elimination of Dominated Strategies 2.6 Multiagent Representations 2.7 Common Knowledge 2.8 Bayesian Games 2.9 Modeling Games with Incomplete Information Exercises 3. Equilibria of Strategic-Form Games 3.1 Domination and Ratonalizability 3.2 Nash Equilibrium 3.3 Computing Nash Equilibria 3.4 Significance of Nash Equilibria 3.5 The Focal-Point Effect 3.6 The Decision-Analytic Approach to Games 3.7 Evolution. Resistance. and Risk Dominance 3.8 Two-Person Zero-Sum Games 3.9 Bayesian Equilibria 3.10 Purification of Randomized Strategies in Equilibria 3.11 Auctions 3.12 Proof of Existence of Equilibrium 3.13 Infinite Strategy Sets Exercises 4. Sequential Equilibria of Extensive-Form Games 4.1 Mixed Strategies and Behavioral Strategies 4.2 Equilibria in Behavioral Strategies 4.3 Sequential Rationality at Information States with Positive Probability 4.4 Consistent Beliefs and Sequential Rationality at All Information States 4.5 Computing Sequential Equilibria 4.6 Subgame-Perfect Equilibria 4.7 Games with Perfect Information 4.8 Adding Chance Events with Small Probability 4.9 Forward Induction 4.10 Voting and Binary Agendas 4.11 Technical Proofs Exercises 5. Refinements of Equilibrium in Strategic Form 5.1 Introduction 5.2 Perfect Equilibria 5.3 Existence of Perfect and Sequential Equilibria 5.4 Proper Equilibria 5.5 Persistent Equilibria 5.6 Stable Sets 01 Equilibria 5.7 Generic Properties 5.8 Conclusions Exercises 6. Games with Communication 6.1 Contracts and Correlated Strategies 6.2 Correlated Equilibria 6.3 Bayesian Games with Communication 6.4 Bayesian Collective-Choice Problems and Bayesian Bargaining Problems 6.5 Trading Problems with Linear Utility 6.6 General Participation Constraints for Bayesian Games with Contracts 6.7 Sender-Receiver Games 6.8 Acceptable and Predominant Correlated Equilibria 6.9 Communication in Extensive-Form and Multistage Games Exercises Bibliographic Note 7. Repeated Games 7.1 The Repeated Prisoners Dilemma 7.2 A General Model of Repeated Garnet 7.3 Stationary Equilibria of Repeated Games with Complete State Information and Discounting 7.4 Repeated Games with Standard Information: Examples 7.5 General Feasibility Theorems for Standard Repeated Games 7.6 Finitely Repeated Games and the Role of Initial Doubt 7.7 Imperfect Observability of Moves 7.8 Repeated Wines in Large Decentralized Groups 7.9 Repeated Games with Incomplete Information 7.10 Continuous Time 7.11 Evolutionary Simulation of Repeated Games Exercises 8. Bargaining and Cooperation in Two-Person Games 8.1 Noncooperative Foundations of Cooperative Game Theory 8.2 Two-Person Bargaining Problems and the Nash Bargaining Solution 8.3 Interpersonal Comparisons of Weighted Utility 8.4 Transferable Utility 8.5 Rational Threats 8.6 Other Bargaining Solutions 8.7 An Alternating-Offer Bargaining Game 8.8 An Alternating-Offer Game with Incomplete Information 8.9 A Discrete Alternating-Offer Game 8.10 Renegotiation Exercises 9. Coalitions in Cooperative Games 9.1 Introduction to Coalitional Analysis 9.2 Characteristic Functions with Transferable Utility 9.3 The Core 9.4 The Shapkey Value 9.5 Values with Cooperation Structures 9.6 Other Solution Concepts 9.7 Colational Games with Nontransferable Utility 9.8 Cores without Transferable Utility 9.9 Values without Transferable Utility Exercises Bibliographic Note 10. Cooperation under Uncertainty 10.1 Introduction 10.2 Concepts of Efficiency 10.3 An Example 10.4 Ex Post Inefficiency and Subsequent Oilers 10.5 Computing Incentive-Efficient Mechanisms 10.6 Inscrutability and Durability 10.7 Mechanism Selection by an Informed Principal 10.8 Neutral Bargaining Solutions 10.9 Dynamic Matching Processes with Incomplete Information Exercises Bibliography Index

博弈论 : 矛盾冲突分析 = Game theory : analysis of conflict

A computer’s memory system is the repository for all the information the computer’s central processing unit (CPU, or processor) uses and produces. A perfect memory system is one that can supply immediately any datum that the CPU requests. This ideal memory is not practically implementable, however, as the three factors of memory capacity, speed, and cost are directly in opposition. By placing smaller faster memories in front of larger, slower, and cheaper memories, the performance of the memory system may approach that of a perfect memory system—at a reasonable cost. The memory hierarchies of modern general-purpose computers generally contain registers at the top, followed by one or more levels of cache memory, main memory (all three are semiconductor memory), and virtual memory (on a magnetic or optical disk). Figure 1 shows a memory hierarchy typical of today’s (1995) commodity systems. Performance of a memory system is measured in terms of latency and bandwidth. The latency of a memory request is how long it takes the memory system to produce the result of the request. The bandwidth of a memory system is the rate at which the memory system can accept requests and produce results. The memory hierarchy improves average latency by quickly returning results that are found in the higher levels of the hierarchy. The memory hierarchy usually reduces bandwidth requirements by intercepting a fraction of the memory requests at higher levels of the hierarchy. Some machines, such as high-performance vector machines, may have fewer levels in the hierarchy—increasing cost for better predictability and performance. Some of these machines contain no caches at all, relying on large arrays of main memory banks to supply very high bandwidth. Pipelined accesses of operands reduce the performance impact of long latencies in these machines. Cache memories are a general solution to improving the performance of a memory system. Although caches are smaller than typical main memory sizes, they ideally contain the most frequently accessed portions of main memory. By keeping the most heavily used data near the CPU, caches can service a large fraction of the requests without needing to access main memory (the fraction serviced is called the hit rate). Caches require locality of reference to work well transparently—they assume that accessed memory words will be accessed again quickly (temporal locality) and that memory words adjacent to an accessed word will be accessed soon after the access in question (spatial locality). When the CPU issues a request for a datum not in the cache (a cache miss), the cache loads that datum and some number of adjacent data (a cache block) into itself from main memory. To reduce cache misses, some caches are associative—a cache may place a given block in one of several places, collectively called a set. This set is content-addressable; a block may be accessed based on an address tag, one of which is coupled with each block. When a new block is brought into a set and the set is full, the cache’s replacement policy dictates which of the old blocks should be removed from the cache to make room for the new. Most caches use an approximation of least recently used

Memory systems

Molecular programming aims to systematically engineer molecular and chemical systems of autonomous function and ever-increasing complexity. A key goal is to develop embedded control circuitry within a chemical system to direct molecular events. Here we show that systems of DNA molecules can be constructed that closely approximate the dynamic behavior of arbitrary systems of coupled chemical reactions. By using strand displacement reactions as a primitive, we construct reaction cascades with effectively unimolecular and bimolecular kinetics. Our construction allows individual reactions to be coupled in arbitrary ways such that reactants can participate in multiple reactions simultaneously, reproducing the desired dynamical properties. Thus arbitrary systems of chemical equations can be compiled into real chemical systems. We illustrate our method on the Lotka–Volterra oscillator, a limit-cycle oscillator, a chaotic system, and systems implementing feedback digital logic and algorithmic behavior.

http://www.pnas.org/content/107/12/5393.full.pdf

DNA as a universal substrate for chemical kinetics

Computer communications

The constantly increasing demand for more computing power can seem impossible to keep up with. However, multicore processors capable of performing computations in parallel allow computers to tackle ever larger problems in a wide variety of applications. This book provides a comprehensive introduction to parallel computing, discussing theoretical issues such as the fundamentals of concurrent processes, models of parallel and distributed computing, and metrics for evaluating and comparing parallel algorithms, as well as practical issues, including methods of designing and implementing shared- and distributed-memory programs, and standards for parallel program implementation, in particular MPI and OpenMP interfaces. Each chapter presents the basics in one place followed by advanced topics, allowing novices and experienced practitioners to quickly find what they need. A glossary and more than 80 exercises with selected solutions aid comprehension. The book is recommended as a text for advanced undergraduate or graduate students and as a reference for practitioners.

Introduction to Parallel Computing

Network security is a complex and challenging problem. The area of network defense mechanism design is receiving immense attention from the research community for more than two decades. However, the network security problem is far from completely solved. Researchers have been exploring the applicability of game theoretic approaches to address the network security issues and some of these approaches look promising. This paper surveys the existing game theoretic solutions which are designed to enhance network security and presents a taxonomy for classifying the proposed solutions. This taxonomy should provide the reader with a better understanding of game theoretic solutions to a variety of cyber security problems.

/pdf/a-survey-of-game-theory-as-applied-to-network-security-ua05d6iand.pdf

A Survey of Game Theory as Applied to Network Security

Cyber-attacks have greatly increased over the years, and the attackers have progressively improved in devising attacks towards specific targets. To aid in identifying and defending against cyber-attacks we propose a cyber attack taxonomy called AVOIDIT (Attack Vector, Operational Impact, Defense, Information Impact, and Target). We use five major classifiers to characterize the nature of an attack: classification by attack vector, classification by operational impact, classification by defense, classification by informational impact, and classification by attack target. Classification by defense is oriented towards providing information to the network administrator regarding attack mitigation or remediation strategies. Contrary to the existing taxonomies, AVOIDIT efficiently classifies blended attacks. We further propose an efficient cause, action, defense, analysis, and target (CADAT) process used to facilitate attack classification. AVOIDIT and CADAT are used by an issue resolution system (IRS) to educate the defender on possible cyber-attacks and the development of potential security policies. We validate the proposed AVOIDIT taxonomy using cyber-attacks scenarios and highlight future work intended to simulate AVOIDIT's use within the IRS.

AVOIDIT: A Cyber Attack Taxonomy

As the number of devices (things) connected to the Internet (Internet of things: IoT) is growing, achieving robust security and privacy (SaP) is becoming increasingly challenging. With the heavy use of medical things (MT), the SaP in the medical domain poses a serious issue that continues to grow. Due to the criticality and sensitivity of the data in the healthcare domain, ensuring the SaP of the Internet of medical things (IoMT) makes matters even more problematic. Lack of proper SaP in IoMT will not only leave patients' privacy at risk but may also put patients' lives at risk. In this paper, we provide a taxonomy of the SaP issues of IoMT. We also provide an approach to quantify IoMT risks and demonstrate how to assess risks in two IoMT devices. This work aims to increase the SaP awareness among IoMT stakeholders by enabling them to identify and quantify potential IoMT SaP risks.

Security and Privacy in the Internet of Medical Things: Taxonomy and Risk Assessment

The emergence of the Internet of Medical Things (IoMT) has introduced a monumental change in facilitating the management of diseases, improving diseases diagnosis and treatment methods, and reducing healthcare cost and errors. This change has greatly impacted the quality of healthcare for both patients and all frontline healthcare workers. However, the IoMT is far from being immune to security and privacy breaches due to the wide variety IoMT vendors and products available on the market as well as the massive number of devices transmitting sensitive medical data wirelessly to the cloud. The lack of security awareness among healthcare users (e.g., patients, medical staff) aggravates the deficiencies and can facilitate attacks that jeopardize the patients’ lives. Therefore, ensuring the security and privacy of the IoMT becomes an urgent issue worthy of further investigation and resolution. Security cannot be planned for, managed, monitored, or controlled if it cannot be measured. However, security assessment poses problems for novice IoMT adopters when choosing security measures that are both sufficient and robust. Accordingly, we developed a web-based IoMT Security Assessment Framework (IoMT-SAF) based on a novel ontological scenario-based approach to recommend security features in IoMT and assess protection and deterrence in IoMT solutions. IoMT-SAF supports the selection of a solution that matches the stakeholder's security objectives and supports the decision-making process. The novelty of IoMT-SAF lies in its granularity, extensibility, as well as its ability to adapt to new stakeholders, and conformance to technology and medical standards.

IoMT-SAF: Internet of Medical Things Security Assessment Framework

While there are significant advances in information technology and infrastructure which offer new opportunities, cyberspace is still far from completely secured. In many cases, the employed security solutions are ad hoc and lack a quantitative decision framework. While they are effective in solving the particular problems they are designed for, they generally fail to respond well in a dynamically changing scenario. To this end, we propose a holistic security approach in this paper. We find that game theory provides huge potential to place such an approach on a solid analytical setting. We consider the interaction between the attacks and the defense mechanisms as a game played between the attacker and the defender (system administrator). In particular, we propose a game theory inspired defense architecture in which a game model acts as the brain. We focus on one of our recently proposed game models, namely imperfect information stochastic game. Although this game model seems to be promising, it also faces new challenges which warrant future attention. We discuss our current ideas on extending this model to address such challenges.

Sajjan G. Shiva

Papers

A Survey of Game Theory as Applied to Network Security

AVOIDIT: A Cyber Attack Taxonomy

Security and Privacy in the Internet of Medical Things: Taxonomy and Risk Assessment

IoMT-SAF: Internet of Medical Things Security Assessment Framework

Game theory for cyber security