Data Mining Practical Machine Learning Tools and Techniques

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

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

[서평]「The Unified Modeling Language User Guide」

Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Pippa Norris. New York: Cambridge University Press, 2002. 303 pp. $60 hbk., $20 pbk. Forecasts that the Internet heralds a world of more democracy and less poverty seem as inflated as dot.com stocks. This rosy view has electronic voting, political chat rooms, and email access re-engaging apathetic publics in politics. Digital technologies redress economic disparities, and the benefits of the Internet percolate down to transform poor societies. Equally exaggerated is the gloom of naysayers. The Internet Age has done little to narrow the gap between rich and poor countries, the information haves and havenots, cyber-skeptics contend. Indeed, digital technologies could create new inequalities and reinforce the dominance of power elites. In her new book, Digital Divide, Pippa Norris, associate director of the Joan Shorenstein Center on the Press, Politics and Public Policy at Harvard University, steps into this fusillade of cyber-hyperbole, lowers the decibel with a well-written and thoughtful examination of Internet use and access in 179 countries and dissects the claims and counter-claims. Her research and findings place her on middle ground, somewhere between current reality and optimism. The Internet era seems to be changing "politics as usual" in a number of countries, expanding and loosening information about governments and politics, allowing the entrance of new political players, and fostering international movements on the environment, women's rights, and other issues across borders. The disappointment is that digital technologies are activating the already politically active and passing up the disengaged and uninterested. A major challenge to digital democracy is the gulf between the United States, Scandinavia, and other early Internet adopters and the rest of the world. That gap is now so wide that at the turn of the century, more than three-quarters of the online community lived in the developed world. Internet use tracks the path of economic and technological development. But that situation could begin to change, Norris says. The Internet is in its technological adolescence. Costs of access are falling. And governments can make a difference if policymakers take the initiative. We have the historical patterns of other communication technologies to study. Norris examines theories of technological diffusion and points out that the American response to the Internet is more akin to the rapid spread of televisions and VCRs than the slower adoption of telephones and radios. American dominance could recede as Internet access grows worldwide. Contrary to what officials of the Bush Administration contend, Norris finds that the digital divide between rich and poor within the United States remains substantial. Europe mirrors that trend. In the long run, the Internet could become more accessible to the excluded: lower income families, minorities, and women. …

Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide

Delegate the smartphone user? Security awareness in smartphone platforms

As both the number and the complexity of cyber-attacks continuously increase, it is becoming evident that current security mechanisms have limited success in detecting sophisticated threats. Stuxnet, Duqu, Flame and Red October have troubled the security community due to their severe complexity and their ability to evade detection - in some cases for several years. The significant technical and financial resources needed for orchestrating such complex attacks are a clear indication that perpetrators are well organized and, likely, working under a state umbrella. In this paper we perform a technical analysis of these advanced persistent threats, highlighting particular characteristics and identifying common patterns and techniques. We also focus on the issues that enabled the malware authors to evade detection from a wide range of security solutions and propose technical countermeasures for strengthening our defenses against similar threats.

The Big Four - What We Did Wrong in Advanced Persistent Threat Detection?

Book review: Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software

Sphinx was a monster in Greek mythology devouring those who could not solve her riddle. In VoIP, a new service in the role of Sphinx provides protection against SPIT (Spam over Internet Telephony) by discriminating human callers from botnets. The VoIP Sphinx tool uses audio CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) that are controlled by an anti-SPIT policy mechanism. The design of the Sphinx service has been formally verified for the absence of side-effects in the VoIP services (robustness), as well as for its DoS-resistance. We describe the principles and innovations of Sphinx, together with experimental results from pilot use cases.

http://delab.csd.auth.gr/~katsaros/TCI2%20SPHINX.pdf

The Sphinx enigma in critical VoIP infrastructures: Human or botnet?

Information systems face several security threats, some of which originate by insiders. This paper presents a novel, interdisciplinary insider threat prediction model. It combines approaches, techniques, and tools from computer science and psychology. It utilizes real time monitoring, capturing the user's technological trait in an information system and analyzing it for misbehavior. In parallel, the model is using data from psychometric tests, so as to assess for each user the predisposition to malicious acts and the stress level, which is an enabler for the user to overcome his moral inhibitions, under the condition that the collection of such data complies with the legal framework. The model combines the above mentioned information, categorizes users, and identifies those that require additional monitoring, as they can potentially be dangerous for the information system and the organization.

Dimitris Gritzalis

Papers

Delegate the smartphone user? Security awareness in smartphone platforms

The Big Four - What We Did Wrong in Advanced Persistent Threat Detection?

Book review: Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software

The Sphinx enigma in critical VoIP infrastructures: Human or botnet?

An insider threat prediction model