Quantifying information security risks using expert judgment elicitation

In the information security business, 30 years of practical and theoretical research has resulted in a fairly sophisticated appreciation for how to judge the qualitative level of risk faced by an enterprise. Based upon that understanding, there is a practical level of protection that a competent security manager can architect for a given enterprise. It would, of course, be better to use a quantitative approach to risk management, but, unfortunately, sufficient quantitative data that has been scientifically collected and analyzed does not exist. There have been many attempts to develop quantitative data using traditional quantitative methods, such as experiments, surveys, and observations, but there are significant weaknesses apparent in each approach. The research described in this paper was constructed to explore the utility of applying the well-established method of expert judgment elicitation to the field of information security. The instrument for eliciting the expert judgments was developed by two information security specialists and two expert judgment analysis specialists. The resultant instrument was validated using a small set of information security experts. The final instrument was used to elicit answers to both the calibration and judgment questions through structured interviews. The data was compiled and analyzed by a specialist in expert judgment analysis. This research illustrates the development of prior distributions for the parameters of models for cyber attacks and uses expert judgment results to develop the distributions.     

There's more than one way to build a bridge

Software engineering is essentially about making good design and implementation decisions, which requires first considering design alternatives. Given the advanced programming tools available today, it is tempting to design by rote using the solution a given tool most readily supports. Although many of the problems that system developers face often result from poor management, sound software engineering can make a difference in at least one key area: the bridge connecting the legacy system with other computer systems     

Dealing with the expert inconsistency in probability elicitation

In this paper, we present and discuss our experience in the task of probability elicitation from experts for the purpose of belief network construction. In our study, we applied four techniques. Three of these techniques are available from the literature, whereas the fourth one is a technique that we developed by adapting a method for the assessment of preferences to the task of probability elicitation. The new technique is based on the analytic hierarchy process (AHP) proposed by Saaty (1980, 1994), and it allows for the quantitative assessment of the expert inconsistency. The method is, in our opinion, very promising and lends itself to be applied more extensively to the task of probability elicitation     

Knowledge management acquisition improvement by using software engineering elicitation techniques

The knowledge externalization phase involves acquiring and transferring the knowledge of individuals to an abstract and effective representation, to organize it, to model it and finally to express this knowledge in an understandable and reusable format. This phase presents some difficulties at the moment to choose the technique that best fit with the knowledge type to be elicited, and sometimes the selected technique is not complete enough to capture all the relevant knowledge for a specific domain. In sum, there are not mechanisms that can be used as a discernment element at the moment to choose the knowledge elicitation technique that better adjust to a particular situation. This paper presents the results obtained from an empirical validation developed to determine the efficiency of knowledge acquisition in the externalization phase of Nonaka’s model, using a set of software engineering elicitation techniques. Efficiency compared with quality of the knowledge acquired can provide a good mechanism to select the most suitable technique to knowledge externalization for each situation.     

多个栈共享内存空间通用算法研究

在分析了传统栈的基础上,提出了一种多个栈共享内存空间的通用算法,以提高内存空间利用率。     

The economic production lot size model extended to include more than one production rate

We study an extension of the economic production lot size model, where more than one production rate can be used during a cycle. Moreover, the production rates, as well as their corresponding runtimes are decision variables. We decompose the problem into two subproblems. First, we show that all production rates should be chosen in the interval between the demand rate and the production rate which minimizes unit production costs, and should be used in an increasing order. Then, given the production rates, we derive closed‐form expressions for all optimal runtimes as well as the minimum average cost. This analysis reveals that it is the size of the setup cost that determines the need for being able to use several production rates. We also show how to derive a near‐optimal solution of the general problem.     

Knowledge elicitation for validation of a neonatal ventilation expert system utilising modified Delphi and focus group techniques

Objective, methods & materials, resultsIt is well known that ventilation strategies for newborn infants may vary significantly between individual doctors. The aim of this study was to elicit knowledge of ventilation management to provide a baseline for evaluating the performance of an expert system for neonatal ventilation (FLORENCE). The modified Delphi method and focus group techniques were used to arrive at consensus management strategies on 40 hypothetical ventilation scenarios. The underlying cognitive processes of the experts were also explored further to assist in the development of the expert system. The strategies arrived at were used to provide a performance level which FLORENCE was tested against. The solutions were judged to be equivalent between FLORENCE and neonatologists in 29 of the 40 cases. In the remaining 11 scenarios; FLORENCE also provided adequate solutions.ConclusionsThe focus group technique was more effective than modified Delphi method in achieving consensus on ventilation management. This consensus on ventilation was used as the baseline to evaluate the performance of an expert system.     

On the reconstruction of lost data in images of more than one band

Starting from the necessity of replacing data of some failed sensors of the LANDSAT-4 Thematic Mapper a methodology for a statistical and objective comparison of various reconstruction techniques for the missing data has been denned. It has been shown that the use of the information contained in a second band gives good results, even in cases where they are not strongly correlated, provided that a proper choice of parameters is made. A method, based on the local relationship between the radiance of the two bands, is suggested which improves on the results obtained by other authors.     

The application of an expert system shell to an unstructured domain of expertise: using expert system technology to teach SSM

Action research is orchestrated by the interaction between theory and practice as exemplified by soft systems methodology (SSM). The use of computers has traditionally been developed out of what has been referred to as the ‘rationalistic’ tradition which represents the search for solutions for pre-determined, logical goals (Winograd & Flores, 1986). Action research anticipates the need to explore and learn about each intervention into human activity, using models thought to be relevant to thinking about the world to help structure the learning process. In comparison, the ‘rationalistic’ tradition seeks universal laws for behaviour and uses validated models of the reality represented by these laws to solve problems. It would seem, therefore, that to translate SSM into a computer-based format would be dialectically opposed to the intellectual framework in which the methodology is seated. However, the authors suggest that there is one area in which a computer-based version of SSM may be useful. This paper describes an exploratory study of the application of expert system technology as an aid to teaching SSM.     

There is more to context than location

Context is a key issue in interaction between human and computer, describing the surrounding facts that add meaning. In mobile computing location is usually used to approximate context and to implement context-aware applications. We propose that ultra-mobile computing, characterized by devices that are operational and operated while on the move (e.g. PDAs, mobile phones, wearable computers), can significantly benefit from a wider notion of context. To structure the field we introduce a working model for context, discuss mechanisms to acquire context beyond location, and application of context-awareness in ultra-mobile computing. We investigate the utility of sensors for context-awareness and present two prototypical implementations — a light-sensitive display and an orientation-aware PDA interface. The concept is then extended to a model for sensor fusion to enable more sophisticated context recognition. Based on an implementation of the model an experiment is described and the feasibility of the approach is demonstrated. Further, we explore fusion of sensors for acquisition of information on more sophisticated contexts.     

Automating land cover mapping of Scotland using expert system and knowledge integration methods

Effective land cover mapping often requires the use of multiple data sources and data interpretation methods, particularly when no one data source or interpretation method provides sufficiently good results. Method-oriented approaches are often only effective for specific land cover class/data source combinations, and cannot be applied when different classification systems or data sources are required or available. Here we present a method, based on Endorsement Theory, of pooling evidence from multiple expert systems and spatial datasets to produce land cover maps. Individual ‘experts’ are trained to produce evidence for or against a class, with this evidence being categorised according to strength. An evidence integration rule set is applied to evidence lists to produce conclusions of different strength regarding individual classes, and the most likely class identified. The only expert system design implemented currently within the methodology is a neural network model, although the system has been designed to accept information from decision trees, fuzzy k-means and Bayesian statistics as well. We have used the technique to produce land cover maps of Scotland using three classification systems of varying complexity. Mapping accuracy varied between 52.6% for a map with 96 classes to 88.8% for a map with eight classes. The accuracy of the maps generated is higher than when individual datasets are used, showing that the evidence integration method applied is suitable for improving land cover mapping accuracy. We showed that imagery was not necessarily the most important data source for mapping where a large number of classes are used, and also showed that even data sources that produce low accuracy scores when used for mapping by themselves do improve the accuracy of maps produced using this integrative approach. Future work in developing the method is identified, including the inclusion of additional expert systems and improvement of the evidence integration, and evaluation carried out of the overall effectiveness of the approach.     

Two-way deterministic automata with two reversals are exponentially more succinct than with one reversal

We prove that limiting the number of reversals from two to one can cause an exponential blow-up in the size of two-way deterministic automaton.     

Improved understorey bamboo cover mapping using a novel hybrid neural network and expert system

The giant panda is an obligate bamboo grazer. Therefore, the availability and abundance of understorey bamboo determines the quantity and quality of panda habitat. However, there is little or no information about the spatial distribution or abundance of bamboo underneath the forest canopy, due to the limitations of traditional remote sensing classification techniques. In this paper, a new method combines an artificial neural network and a GIS expert system in order to map understorey bamboo in the Qinling Mountains of south‐western China. Results from leaf‐off ASTER imagery, using a neural network and an expert system, were evaluated for their suitability to quantify understorey bamboo. Three density classes of understorey bamboo were mapped, first using a neural network (overall accuracy 64.7%, Kappa 0.45) and then using an expert system (overall accuracy 62.1%, Kappa 0.43). However, when using the results of the neural network classification as input into the expert system, a significantly improved mapping accuracy was achieved with an overall accuracy of 73.8% and Kappa of 0.60 (average z‐value = 3.35, p = 0.001). Our study suggests that combining a neural network with an expert system makes it possible to successfully map the cover of understorey species such as bamboo in complex forested landscapes (e.g. coniferous‐dominated and dense canopy forests), and with higher accuracy than when using either a neural network or an expert system.     

Reengineering: more than meets the eye

Changes too often leave us shaken, unsteady and unable to perform, yet hospital reengineering usually means major, lingering change. Systematic reengineering, properly implemented, can reduce the strain.     

Constraint-based optimization and utility elicitation using the minimax decision criterion

In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which multiple users have distinct preferences. However, making suitable decisions requires that the preferences of a specific user for different configurations be articulated or elicited, something generally acknowledged to be onerous. We address two problems associated with preference elicitation: computing a best feasible solution when the user's utilities are imprecisely specified; and developing useful elicitation procedures that reduce utility uncertainty, with minimal user interaction, to a point where (approximately) optimal decisions can be made. Our main contributions are threefold. First, we propose the use of minimax regret as a suitable decision criterion for decision making in the presence of such utility function uncertainty. Second, we devise several different procedures, all relying on mixed integer linear programs, that can be used to compute minimax regret and regret-optimizing solutions effectively. In particular, our methods exploit generalized additive structure in a user's utility function to ensure tractable computation. Third, we propose various elicitation methods that can be used to refine utility uncertainty in such a way as to quickly (i.e., with as few questions as possible) reduce minimax regret. Empirical study suggests that several of these methods are quite successful in minimizing the number of user queries, while remaining computationally practical so as to admit real-time user interaction.     

There is more to monitoring a nuclear power plant than meets the eye

A fundamental challenge in studying cognitive systems in context is how to move from the specific work setting studied to a more general understanding of distributed cognitive work and how to support it. We present a series of cognitive field studies that illustrate one response to this challenge. Our focus was on how nuclear power plant (NPP) operators monitor plant state during normal operating conditions. We studied operators at two NPPs with different control room interfaces. We identified strong consistencies with respect to factors that made monitoring difficult and the strategies that operators have developed to facilitate monitoring. We found that what makes monitoring difficult is not the need to identify subtle abnormal indications against a quiescent background, but rather the need to identify and pursue relevant findings against a noisy background. Operators devised proactive strategies to make important information more salient or reduce meaningless change, create new information, and off-load some cognitive processing onto the interface. These findings emphasize the active problem-solving nature of monitoring, and highlight the use of strategies for knowledge-driven monitoring and the proactive adaptation of the interface to support monitoring. Potential applications of this research include control room design for process control and alarm systems and user interfaces for complex systems.     

浅谈人造物比自然物更美

在21世纪这个多元文化并存的现代化国际化的世界,自然物是美的,我们要加以重视,然而人造物的美是建立在自然物美的基础之上的,人造物的美也是通过对于自然物美的艺术创造来实现的,给予了自然物更多非同寻常的意义,丰富了其功能性与实用性,将简单的物与其功能需求联系起来,企图寻求一种高于自然的艺术创造的意向,赋予了感情和生命的活力。人造物改变着现代社会的生活,孕育着人类智慧,比自然物更美。     

Knowledge map: An approach to knowledge acquisition in developing engineering expert systems

This paper addresses the critical issues of knowledge acquisition in developing knowledge-based expert systems for engineering tasks. First, it reviews the role of knowledge acquisition and its current practice in expert system development. Then, a new approach based on three stages of knowledge refinement is suggested to improve the process of knowledge acquisition. This approach, calledrule verification without rule construction, is proposed to allow knowledge engineers and domain experts to experience a more intimate and balanced role in developing intelligent systems. The communication tool developed for this concept is calledknowledge map, which provides a systematic way of indexing and quantifying a piece of knowledge in the problem space by defining important attributes as the axes of the map. This approach is demonstrated by constructing a twodimensional map for a knowledge-based engineering design system, IDRILL, which we are currently developing. Future expansions of this knowledge acquisition technique are summarized as the conclusions of this paper.This paper was presented in part at the 1986 ASME International Computers in Engineering Conference in Chicago, IL, and appeared in the proceedings of that conference.