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

International Journal of Computer and Applications

The Grid 2: Blueprint for a New Computing Infrastructure

Reading a book is also kind of better solution when you have no enough money or time to get your own adventure. This is one of the reasons we show the introduction to functional magnetic resonance imaging principles and techniques as your friend in spending the time. For more representative collections, this book not only offers it's strategically book resource. It can be a good friend, really good friend with much knowledge.

Introduction to Functional Magnetic Resonance Imaging, Principles and TechniquesIntroduction to Functional Magnetic Resonance Imaging, Principles and Techniques. By BuxtonR. B.. Cambridge University Press, Cambridge2002. ISBN 0-521-58113-3. 536 pages 134 line diagrams, 34 halftone figures. Price hardback: GBP 95.00.

Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches.

Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

Data preprocessing for anomaly based network intrusion detection : a review

This paper presents an efficient optical image cryptosystem based on double random phase encoding (DRPE) and Arnold’s Cat map. The proposed image cryptosystem utilizes two layers to enhance the security level over the classical DRPE. The first layer is a pre-processing layer, which is performed with the chaotic Cat map on the original image. In the second layer, the classical DRPE is utilized. Matlab simulation experiments show that the proposed optical image cryptosystem enhances the security level of the DRPE, and at the same time it has a better immunity to noise.

Optical image cryptosystem using double random phase encoding and Arnold’s Cat map

http://www.osdp.cs.tsukuba.ac.jp/kameda/MyPapers/MyJournals/ComOpRes0.pdf

Numerical studies on a paradox for non-cooperative static load balancing in distributed computer systems

This paper introduces a secure chaos-based model for ciphering and deciphering of digital images. The proposed approach is composed of successive confusion and diffusion stages. The confusion stage is repeated n rounds using a different key in each round. The output of the confusion stage is subjected to diffusion stage which is repeated m rounds with a different key for each round. The nested iterations in the confusion and diffusion stages with a different key for each round enlarges the key space which enhances the proposed image cryptosystem security level. A security investigation is done on a family of 2D chaotic confusion maps to select the one with highest security level to be used with the proposed image cryptosystem. The results demonstrated that the Standard map has the highest security level among the examined 2D chaotic confusion maps because it is more complicated and it has a large key space. The proposed image cryptosystem is compared to other three recent image cryptosystems using different security analysis factors including statistical tests, key space analysis, information entropy test, maximum deviation analysis, irregular deviation analysis, and avalanche effect differential analysis. The results demonstrated that, the proposed image cryptosystem with Standard map outperforms all of the other examined image encryption techniques from security point of view.

Chaos-based model for encryption and decryption of digital images

In this research paper, an adaptive difference expansion-based reversible data hiding technique with the capability of embedding either three bits or two bits or one bit for each pixel and which can deal with color image is presented. To embed and extract data, the proposed technique has some salient features such as its capability to control the embedding capacity by using three global embedding parameters. These parameters are computed using the statistics of the embedded pixel surrounding pixels. Also, the data embedding steps in the proposed scheme can be reversed to completely retrieve the cover image free from any deformation. Furthermore, in the proposed technique, no reference images or memorization of the embedded pixel positions are needed in the data extraction process. A course of experiments is conducted, and the results demonstrated that the proposed technique outperforms other similar techniques in terms of payload capacity and PSNR.

Adaptive Difference Expansion-Based Reversible Data Hiding Scheme for Digital Images

In this paper, we propose an efficient and a scalable protocol for secure multicast communication This protocol is based on the Iolus and the logical key hierarchy protocols It divides the whole group into several subgroups as in the Iolus protocol Each subgroup in turn is organized in a logical key hierarchy as in the LKH protocol This decomposition reduces the complexity for a member join or leave form O(n) to O(logm), where n is the number of the whole group members and m is the number of each subgroup members The performance of the proposed protocol is compared with that of the Simple App, Iolus and LKH protocols The comparison is undertaken according to the computational overhead, communication overhead, storage overhead, and message size The results show that the proposed protocol enhances the group performance in terms of computation overhead, and communication overhead especially at the leave operation

/pdf/a-scalable-and-distributed-security-protocol-for-multicast-5c5j8od9ya.pdf

S. F. El-Zoghdy

Papers

Optical image cryptosystem using double random phase encoding and Arnold’s Cat map

Numerical studies on a paradox for non-cooperative static load balancing in distributed computer systems

Chaos-based model for encryption and decryption of digital images

Adaptive Difference Expansion-Based Reversible Data Hiding Scheme for Digital Images

A Scalable and Distributed Security Protocol for Multicast Communications