THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Security administration of large systems is complex, but it can be simplified by a role-based access control approach. This article explains why RBAC is receiving renewed attention as a method of security administration and review, describes a framework of four reference models developed to better understand RBAC and categorizes different implementations, and discusses the use of RBAC to manage itself.

Role-based access control models

National Institute of Standards and Technology における超伝導研究及び生活

In this article we propose a standard for role-based access control (RBAC). Although RBAC models have received broad support as a generalized approach to access control, and are well recognized for their many advantages in performing large-scale authorization management, no single authoritative definition of RBAC exists today. This lack of a widely accepted model results in uncertainty and confusion about RBAC's utility and meaning. The standard proposed here seeks to resolve this situation by unifying ideas from a base of frequently referenced RBAC models, commercial products, and research prototypes. It is intended to serve as a foundation for product development, evaluation, and procurement specification. Although RBAC continues to evolve as users, researchers, and vendors gain experience with its application, we feel the features and components proposed in this standard represent a fundamental and stable set of mechanisms that may be enhanced by developers in further meeting the needs of their customers. As such, this document does not attempt to standardize RBAC features beyond those that have achieved acceptance in the commercial marketplace and research community, but instead focuses on defining a fundamental and stable set of RBAC components. This standard is organized into the RBAC Reference Model and the RBAC System and Administrative Functional Specification. The reference model defines the scope of features that comprise the standard and provides a consistent vocabulary in support of the specification. The RBAC System and Administrative Functional Specification defines functional requirements for administrative operations and queries for the creation, maintenance, and review of RBAC sets and relations, as well as for specifying system level functionality in support of session attribute management and an access control decision process.

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Proposed NIST standard for role-based access control

This newly revised edition of the Artech House bestseller, Role-Based Access Control, offers you the very latest details on this sophisticated security model aimed at reducing the cost and complexity of security administration for large networked applications. The second edition provides more comprehensive and updated coverage of access control models, new Rbac standards, new in-depth case studies and discussions on role engineering and the design of role-based systems. The book shows you how Rbac simplifies security administration by using roles, hierarchies, and constraints to manage the review and control of organizational privileges. Moreover, it explains how Rbac makes it possible to specify many types of enterprise security policies. This unique resource covers all facets of Rbac, from its solid model-theoretic foundations to its implementation within commercial products. You learn how to use Rbac to emulate other access control models and find frameworks and tools for administering Rbac. Research prototypes that have incorporated Rbac into various classes of software like Wfms, Web server, Os (Unix) and Java (Jee) are reviewed. Products implementing Rbac features such as relational Dbms and Enterprise Security Administration (Esa) systems are described to serve as a guide to the state of practice of Rbac.

Role-based access control

This paper describes a unified model for role-based access control (RBAC). RBAC is a proven technology for large-scale authorization. However, lack of a standard model results in uncertainty and confusion about its utility and meaning. The NIST model seeks to resolve this situation by unifying ideas from prior RBAC models, commercial products and research prototypes. It is intended to serve as a foundation for developing future standards. RBAC is a rich and open-ended technology which is evolving as users, researchers and vendors gain experience with it. The NIST model focuses on those aspects of RBAC for which consensus is available. It is organized into four levels of increasing functional capabilities called flat RBAC, hierarchical RBAC, constrained RBAC and symmetric RBAC. These levels are cumulative and each adds exactly one new requirement. An alternate approach comprising flat and hierarchical RBAC in an ordered sequence and two unordered features—constraints and symmetry—is also presented. The paper furthermore identifies important attributes of RBAC not included in the NIST model. Some are not suitable for inclusion in a consensus document. Others require further work and agreement before standardization is feasible.

The NIST model for role-based access control: towards a unified standard

This document provides Federal agencies with a definition of attribute based access control (ABAC). ABAC is a logical access control methodology where authorization to perform a set of operations is determined by evaluating attributes associated with the subject, object, requested operations, and, in some cases, environment conditions against policy, rules, or relationships that describe the allowable operations for a given set of attributes. This document also provides considerations for using ABAC to improve information sharing within organizations and between organizations while maintaining control of that information.

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Guide to Attribute Based Access Control (ABAC) Definition and Considerations

While Mandatory Access Controls (MAC) are appropriate for multilevel secure military applications, Discretionary Access Controls (DAC) are often perceived as meeting the security processing needs of industry and civilian government. This paper argues that reliance on DAC as the principal method of access control is unfounded and inappropriate for many commercial and civilian government organizations. The paper describes a type of non-discretionary access control - role-based access control (RBAC) - that is more central to the secure processing needs of non-military systems than DAC.

D. Richard Kuhn

Papers

Proposed NIST standard for role-based access control

Role-based access control

The NIST model for role-based access control: towards a unified standard

Guide to Attribute Based Access Control (ABAC) Definition and Considerations

Role-Based Access Controls