Uncertainty in Trust: A Risk-Aware Approach

2016 ◽  
Vol 24 (05) ◽  
pp. 703-737
Author(s):  
Sadegh Dorri Nogoorani ◽  
Rasool Jalili
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Confidence Interval ◽  
Confidence Intervals ◽  
Risk Model ◽  
Trust Model ◽  
Evidence Based ◽  
Trust Value ◽  
Trust Models ◽  
Simulation Results

Uncertainty and its imposed risk have significant impacts on decision-making. However, both are disregarded in many trust-based applications. In this paper, we propose a risk-aware approach to explicitly take uncertainty of trust and its effects into account. Our approach consists of a trust, a confidence, and a risk model. We do not prescribe a specific trust model, and any probabilistic trust model can be empowered by our approach. The confidence model calculates the uncertainty of the trust model in the form of a confidence interval, and is independent of the inner-workings of the trust model. This interval is used by the utility-based risk model which assesses the effects of uncertainty on trust-based decisions. We evaluated our approach by a four-state HMM-based simulated trustee, and employed the Beta, HMM and evidence-based trust models. We proposed and compared different methods for calculating confidence intervals, as well as methods for determining the risk and opportunity of a trust-based interaction. The results demonstrate how our approach should be used to improve the correctness of decision-making in trust-based applications. According to the statistical analysis of the simulation results, confidence intervals can properly represent the trust value and its uncertainty, and strongly improve trust-based decisions.

scholarly journals Statistical analysis of cytogenetic data

2021 ◽  
Vol 28 ◽  
pp. 146-150
Author(s):  
L. A. Atramentova
Keyword(s):  
Data Structure ◽  
Statistical Analysis ◽  
Confidence Interval ◽  
Statistical Method ◽  
Confidence Intervals ◽  
Study Design ◽  
Cytogenetic Study ◽  
Data Set ◽  
Statistical Errors ◽  
Cytogenetic Data

Using the data obtained in a cytogenetic study as an example, we consider the typical errors that are made when performing statistical analysis. Widespread but flawed statistical analysis inevitably produces biased results and increases the likelihood of incorrect scientific conclusions. Errors occur due to not taking into account the study design and the structure of the analyzed data. The article shows how the numerical imbalance of the data set leads to a bias in the result. Using a dataset as an example, it explains how to balance the complex. It shows the advantage of presenting sample indicators with confidence intervals instead of statistical errors. Attention is drawn to the need to take into account the size of the analyzed shares when choosing a statistical method. It shows how the same data set can be analyzed in different ways depending on the purpose of the study. The algorithm of correct statistical analysis and the form of the tabular presentation of the results are described. Keywords: data structure, numerically unbalanced complex, confidence interval.

scholarly journals A Trust-Based Predictive Model for Mobile Ad Hoc Networks

2021 ◽  
Vol 11 (03) ◽  
pp. 13-23
Author(s):  
K. Divya ◽  
B. Srinivasan
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Ad Hoc ◽  
Trust Model ◽  
Trust Value ◽  
Trust Models ◽  
Indirect Trust ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
The Internet Of Things

The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.

scholarly journals Statistical Analysis of the Reliability of a Decision Obtained by the TOPSIS Method

2019 ◽  
Vol 54 (1) ◽  
pp. 110-118 ◽  
Author(s):  
Rūta Simanavičienė ◽  
Jovita Cibulskaitė
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Initial Data ◽  
Confidence Intervals ◽  
Engineering Industry ◽  
Topsis Method ◽  
Multicriteria Decision ◽  
Data Errors ◽  
Measure Reliability ◽  
Statistical Analysis Methods

The tasks of making the most appropriate decisions taking into account a number of criteria are dealt with in variousfields such as engineering, industry, finance, economics and others. If the aim is to arrange the alternatives in a priority lineaccording to quantitative attributes, then multiattribute decision-making methods are suitable. Analysts using these methods usuallydo not take into account initial data errors – deviations in attribute values, in which case the decision may be unreliable. In thisarticle, several statistical analysis methods are proposed for the multicriteria decision to measure reliability: formulation of statisticalhypotheses and calculation of confidence intervals for parameters. Based on statistical analysis results, conclusions about thereliability of a multicriteria decision obtained using the TOPSIS method are formulated.

scholarly journals Robust Confidence Intervals for the Population Mean Alternatives to the Student-t Confidence Interval

2020 ◽  
Vol 18 (1) ◽  
pp. 2-15
Author(s):  
Jennifer E. V. Lloyd ◽  
Jacqui Boonstra ◽  
Barry Forer ◽  
Rush Hershler ◽  
Constance Milbrath ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Confidence Interval ◽  
Knowledge Translation ◽  
Confidence Intervals ◽  
Research Methodology ◽  
Theoretical Basis ◽  
Population Based ◽  
Youth Health ◽  
Key Terms ◽  
Data Linkages

Population-based, person-specific, longitudinal child and youth health and developmental data linkages involve connecting combinations of specially-collected data and administrative data for longitudinal population research purposes. This glossary provides definitions of key terms and concepts related to their theoretical basis, research infrastructure, research methodology, statistical analysis, and knowledge translation.

Moneyball for Knowledge Management

2015 ◽  
pp. 51-64
Author(s):  
Douglas Weidner ◽  
John Girard
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Statistical Analysis ◽  
Operations Research ◽  
Management Science ◽  
Evidence Based ◽  
New Techniques ◽  
Maturity Models ◽  
Baseball Team ◽  
Evidence Based Decision Making

Moneyball is Michael Lewis's story about the use of statistical analysis and modeling by the Oakland A's baseball team to maximize games won per payroll dollar. When new techniques—analytics and evidence-based decision making—get such visibility their time may have arrived. Such analytic techniques have been known for some time as Management Science or Operations Research, but they are possibly not very well known by the Knowledge Management (KM) community. So, how will KM avail itself of this emerging capability? This chapter addresses emerging analytics by focusing on their use in the next generation of maturity models for KM.

scholarly journals Confidence Intervals for the Coefficient of Variation in a Normal Distribution with a Known Population Mean

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Wararit Panichkitkosolkul
Keyword(s):  
Confidence Interval ◽  
Normal Distribution ◽  
Confidence Intervals ◽  
Coefficient Of Variation ◽  
Coverage Probability ◽  
Normal Approximation ◽  
Monte Carlo Simulation Study ◽  
Population Mean ◽  
Expected Length ◽  
Simulation Results

This paper presents three confidence intervals for the coefficient of variation in a normal distribution with a known population mean. One of the proposed confidence intervals is based on the normal approximation. The other proposed confidence intervals are the shortest-length confidence interval and the equal-tailed confidence interval. A Monte Carlo simulation study was conducted to compare the performance of the proposed confidence intervals with the existing confidence intervals. Simulation results have shown that all three proposed confidence intervals perform well in terms of coverage probability and expected length.

scholarly journals A Statistical Primer: Understanding Descriptive and Inferential Statistics

2007 ◽  
Vol 2 (1) ◽  
pp. 32 ◽  
Author(s):  
Gillian Byrne
Keyword(s):  
Decision Making ◽  
Statistical Analysis ◽  
Analysis Of Variance ◽  
Evidence Based Practice ◽  
Statistical Techniques ◽  
Evidence Based ◽  
Inferential Statistics ◽  
Chi Square ◽  
Evidence Based Decision Making

As libraries and librarians move more towards evidence-based decision making, the data being generated in libraries is growing. Understanding the basics of statistical analysis is crucial for evidence-based practice (EBP), in order to correctly design and analyze research as well as to evaluate the research of others. This article covers the fundamentals of descriptive and inferential statistics, from hypothesis construction to sampling to common statistical techniques including chi-square, correlation, and analysis of variance (ANOVA).

scholarly journals Trusted Cloud Platform for Cloud Infrastructure

2013 ◽  
Vol 10 (8) ◽  
pp. 1884-1891
Author(s):  
Punit Gupta ◽  
Deepika Agrawal
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Cloud Service ◽  
Trust Model ◽  
Cloud Infrastructure ◽  
Service Model ◽  
Infrastructure As A Service ◽  
Trust Value ◽  
Trust Models ◽  
Computing Framework

Reliability and trust Models are used to enhance secure , reliable scheduling , load balancing and QoS in cloud and Distributed environment. Trust models that are being used in Distributed and Grid environment, does not qualify cloud computing environment requirements. Since the parameters that have being taken into consideration in these trust models, does not fit in the cloud Infrastructure As A Service, a suitable trust model is proposed based on the existing model that is suitable for trust value management for the cloud IaaS parameters. Based on the above achieved trust values,  trust based scheduling and load balancing  is done for better allocation of resources and enhancing the QOS of services been provided to the users. In this paper, an trust based cloud computing framework is proposed using trust model ,trust based scheduling and load balancing algorithms. Here we describe the design and development of trusted Cloud service model for cloud Infrastructure as a service (IaaS) known as VimCloud .VimCloud an open source cloud computing framework that implements the tusted Cloud Service Model and  trust based scheduling and load balancing algorithm . However one of the major issues in cloud IaaS is to ensure reliability and security or used data and computation. Trusted cloud service model ensures that user virual machine executes only on trusted cloud node, whose integrity and reliability is known in term of trust value . VimCloud shown practical in term of performace which is better then existing models.

scholarly journals A Trust-Based Predictive Model for Mobile Ad Hoc Network in Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1467 ◽  
Author(s):  
Waleed Alnumay ◽  
Uttam Ghosh ◽  
Pushpita Chatterjee
Keyword(s):  
Internet Of Things ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Trust Model ◽  
Trust Value ◽  
Trust Models ◽  
Indirect Trust ◽  
Mobile Ad Hoc ◽  
Hoc Networks ◽  
The Internet Of Things

The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. A Beta probabilistic distribution is used to combine different trust evidences and direct trust has been calculated. The theory of ARMA/GARCH has been used to combine the recommendation trust evidences and predict the resultant trust value of each node in multi-step ahead. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.

Trust Models in Grid Computing: A Review

2019 ◽  
Vol 13 (2) ◽  
pp. 94-100
Author(s):  
Dolly Sharma ◽  
Shailendra Singh ◽  
Mamta Mittal
Keyword(s):  
Grid Computing ◽  
Real World ◽  
Trust Management ◽  
Evaluation Model ◽  
Three Dimensional ◽  
Trust Model ◽  
Trust Evaluation ◽  
Grid Environment ◽  
Trust Value ◽  
Trust Models

Background: Grid computing relates to a pool of resources to be shared by users in Grid Environment. Security of the resources from users and vice-versa is a significant issue. This is where the notion of trust comes into existence. A number of researchers have proposed models for evaluation of trust in grid computing, but they fail to spot one or the other parameters for trust evaluation. The essence of trust models in grid computing is that they offer autonomic trust management. An autonomic trust model has been patented by Z. Yan and C. Prehofer in 2009. Another patent was published by Anna University in 2010 to evaluate the trustworthiness of a resource provider in Grid environment. Objective: This paper firstly focuses and illustrates these essential parameters. Based on these parameters, further, a comparison of some existing models for trust evaluation is shown. Finally, common parameters missed out by various models have been highlighted giving way for improvements of Trust model. Methods: A Trust evaluation model has been proposed by us previously based on a number of real-world trust evaluation parameters. This model sees trust as a three-dimensional entity. Trust is based on Dempter Shafer’s theory in which trust is calculated mathematically. Results: Software trust needs to be calculated mathematically. There are a large number of real-world parameters that need to be included for evaluating trust. Conclusion: As trust models in research are based on simulation techniques, so it is important to include real-world factors that affect trust value of one entity on other. Some of those parameters, missed by most of the models have been identified for inclusion in future trust models.

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