A robust continuous model for evidential reasoning

A 2-D model for evidential reasoning is proposed, in which the belief function of evidence is represented as a belief density function which can be in a continuous or discrete form. A vector form of mutual dependency relationship of the evidence is considered and a dependency propagation theorem is proved. This robust method can resolve the conflicts resulting from either the mutual dependency among evidences or the structural dependency in an inference network due to the evidence combination order. Belief conjunction, belief combination, belief propagation procedures, and AND/OR operations of an inference network based on the proposed 2-D model are all presented, followed by some examples demonstrating the advantages of this method over the conventional methods.     

An integrated trust and reputation model for open multi-agent systems

Trust and reputation are central to effective interactions in open multi-agent systems (MAS) in which agents, that are owned by a variety of stakeholders, continuously enter and leave the system. This openness means existing trust and reputation models cannot readily be used since their performance suffers when there are various (unforseen) changes in the environment. To this end, this paper presents FIRE, a trust and reputation model that integrates a number of information sources to produce a comprehensive assessment of an agent’s likely performance in open systems. Specifically, FIRE incorporates interaction trust, role-based trust, witness reputation, and certified reputation to provide trust metrics in most circumstances. FIRE is empirically evaluated and is shown to help agents gain better utility (by effectively selecting appropriate interaction partners) than our benchmarks in a variety of agent populations. It is also shown that FIRE is able to effectively respond to changes that occur in an agent’s environment.     

A goal-oriented trust model for virtual organization creation

Virtual organization (VO) is a main organizational paradigm for enterprises to collaborate in the rapidly changing environment. Advances in information and communication technologies are accelerating collaboration among enterprises in different domains as well as unknown enterprises. In this environment, an enterprise faces more chances to cooperate with other enterprises through the internet. Trust is a key concept in many kinds of interactions, allowing an enterprise to act under uncertainty and with the risk of negative consequences. To minimize the operating risk and guarantee the success of a VO, trust evaluation of potential partners should be considered during the partner selection process. However, trust evaluation methods in the literature have limitations in applying them to small and medium enterprises because they are based on evaluation of human experts. In this paper, a goal-oriented trust model is proposed to evaluate the trust values of enterprises. In the context, trust is the probability that a trustee satisfies the goals when it completes assigned tasks. This paper introduces the concept of a goal-oriented trust model with the core constructs of a goal, a project, a task, and a capability. It further addresses an example of applying the proposed model to the partner selection process of a project-based VO creation.     

A trust model for popular smart home devices

International Journal of Information Security - Nowadays, smart home devices like Amazon Echo and Google Home have reached mainstream popularity. Being in the homes of users, these devices are...     

A new uncertainty measure for belief networks with applications tooptimal evidential inferencing

We are concerned with the problem of measuring the uncertainty in a broad class of belief networks, as encountered in evidential reasoning applications. In our discussion, we give an explicit account of the networks concerned, and call them the Dempster-Shafer (D-S) belief networks. We examine the essence and the requirement of such an uncertainty measure based on well-defined discrete event dynamical systems concepts. Furthermore, we extend the notion of entropy for the D-S belief networks in order to obtain an improved optimal dynamical observer. The significance and generality of the proposed dynamical observer of measuring uncertainty for the D-S belief networks lie in that it can serve as a performance estimator as well as a feedback for improving both the efficiency and the quality of the D-S belief network-based evidential inferencing. We demonstrate, with Monte Carlo simulation, the implementation and the effectiveness of the proposed dynamical observer in solving the problem of evidential inferencing with optimal evidence node selection     

PeerTrust: supporting reputation-based trust for peer-to-peer electronic communities

Peer-to-peer (P2P) online communities are commonly perceived as an environment offering both opportunities and threats. One way to minimize threats in such communities is to use community-based reputations to help estimate the trustworthiness of peers. We present PeerTrust - a reputation-based trust supporting framework, which includes a coherent adaptive trust model for quantifying and comparing the trustworthiness of peers based on a transaction-based feedback system, and a decentralized implementation of such a model over a structured P2P network. PeerTrust model has two main features. First, we introduce three basic trust parameters and two adaptive factors in computing trustworthiness of peers, namely, feedback a peer receives from other peers, the total number of transactions a peer performs, the credibility of the feedback sources, transaction context factor, and the community context factor. Second, we define a general trust metric to combine these parameters. Other contributions of the paper include strategies used for implementing the trust model in a decentralized P2P environment, evaluation mechanisms to validate the effectiveness and cost of PeerTrust model, and a set of experiments that show the feasibility and benefit of our approach.     

Disseminating trust information in wearable communities

This paper describes a framework for managing and distributing trust information in a community of mobile and wearable computer users. Trust information in the form of reputations are used to aid users during their social interactions with the rest of the community.     

Precursors of trust in virtual health communities: A hierarchical investigation

Lack of trust can have a negative influence on consumers’ willingness to share and adopt information in virtual health communities. However, not much is known about factors that influence the development of trust in such communities. This paper examined precursors of trust in virtual health communities. Data were collected from 361 users of virtual health community sites in South Africa. Structural equation modelling using version 23 of AMOS was used to analyse the data. The findings show that information usefulness, community responsiveness and shared vision have significant influence on consumers’ overall trust in health-related virtual communities. The findings, however, show differences in the extent to which precursor variables influence different dimensions of overall trust. The study provides insights that can help managers of such sites to effectively foster the development of trust in their communities.     

PKI互操作性的一种新的信任模型

PKI是解决电子商务和电子政务安全的有效途径。针对不同国家和不同组织采用不同的PKI安全政策和实现引发的互操作性问题,提出了一种新的CA环状信任模型——网关型CA来解决PKI的互操作性。     

基于SAML的信任移植模型

分析比较如下几种信任移植方案:基于数据冗余技术,基于Cookie技术和基于CAS技术.发现这几种解决方案并不能很好的解决,整合不同企业的相关服务时遇到的信任移植问题.针对现有方案的不足,本文结合SAML标准及其模型,提出了一个信任移植模型.该模型具有平台独立性,信息安全性,并且能对合作企业的相关服务进行有效的整合,更能适应现有的电子商务模式.     

A modified trust region algorithm for nonlinear equations with new updating rule of trust region radius

In this article, we present a trust region algorithm for the nonlinear equations with a new updating rule of the trust region radius, which takes some function of the residual. We show that under the local error bound condition which is weaker than the non-singularity, the new algorithm converges quadratically to some solution of the nonlinear equations. Numerical results show that the new algorithm performs very well for some singular nonlinear equations.     

A dynamic bibliometric model for identifying online communities

Predictive modelling of online dynamic user-interaction recordings and community identification from such data becomes more and more important with the widespread use of online communication technologies. Despite of the time-dependent nature of the problem, existing approaches of community identification are based on static or fully observed network connections. Here we present a new, dynamic generative model for the inference of communities from a sequence of temporal events produced through online computer- mediated interactions. The distinctive feature of our approach is that it tries to model the process in a more realistic manner, including an account for possible random temporal delays between the intended connections. The inference of these delays from the data then forms an integral part of our state-clustering methodology, so that the most likely communities are found on the basis of the likely intended connections rather than just the observed ones. We derive a maximum likelihood estimation algorithm for the identification of our model, which turns out to be computationally efficient for the analysis of historical data and it scales linearly with the number of non-zero observed (L + 1)-grams, where L is the Markov memory length. In addition, we also derive an incremental version of the algorithm, which could be used for real-time analysis. Results obtained on both synthetic and real-world data sets demonstrate the approach is flexible and able to reveal novel and insightful structural aspects of online interactions. In particular, the analysis of a full day worth synchronous Internet relay chat participation sequence, reveals the formation of an extremely clear community structure.     

A linguistic consensus model for Web 2.0 communities

Web 2.0 communities are a quite recent phenomenon which involve large numbers of users and where communication between members is carried out in real time. Despite of those good characteristics, there is still a necessity of developing tools to help users to reach decisions with a high level of consensus in those new virtual environments. In this contribution a new consensus reaching model is presented which uses linguistic preferences and is designed to minimize the main problems that this kind of organization presents (low and intermittent participation rates, difficulty of establishing trust relations and so on) while incorporating the benefits that a Web 2.0 community offers (rich and diverse knowledge due to a large number of users, real-time communication, etc.). The model includes some delegation and feedback mechanisms to improve the speed of the process and its convergence towards a solution of consensus. Its possible application to some of the decision making processes that are carried out in the Wikipedia is also shown.     

A novel trust evolution algorithm based on a quantum-like model of computational trust

Cognition, Technology & Work - Trust models play an important role in decision support systems and computational environments in general. The common goal of the existing trust models is to...     

A text categorisation tool for open source communities based on semantic analysis

Open source software (OSS) projects are supported by communities interacting through software repositories and mailing lists. Thousands of contributors participate in the development of the projects although they rarely meet each other. The result is a huge archived repository with thousands of questions, answers and contributions usually difficult to explore. We propose a tool based on semantic analysis for both performing an automatic knowledge discovery and a categorisation of the content of mailing lists repositories. Semantic analysis is a practical method for extracting and inferring relations of words in passages of discourse, producing measures of relations among words or passages that are well correlated with semantic similarity. The objective of this article is two-fold: (1) to develop a text categorisation tool based on indexing terms and semantic annotation, and (2) to apply the developed tool to extract the main dimensions related to knowledge sharing activities in virtual communities. Debian Linux ports to embedded processors are used as a case study to accomplish the proposed double objective.     

A computational trust model for access control in P2P

Trust brings a new method for building scalable and fine-grained access control mechanism in P2P systems. The quantificational expression of trust and the calculation of trust in a trust network are the basis of trust degree based access control. In this paper, the properties of trust is analyzed by referring to the fruits from social science; the semantics of trust in the context of access control is described, and a trust degree based access control model named TDBAC is introduced. Basing on the propertie...     

A distributed trust management model for mobile P2P networks

In this paper we propose a distributed Trust Management Model (DTMM) for constructing much shorter and more robust trust chains in mobile p2p networks. With DTMM, each moving object within the same group tends to have a high probability of keeping stable distances from each other. The main contribution of this model is to predict the future availability of wireless links and lead to fast generating valid trust evidences. A major difference between DTMM and many existing models in trust literature is that DTMM does not rely on any fixed networking infrastructure, and therefore is able to adapt to both high mobility environments. Our work appears to be the first attempt to research the relationship between mobile patterns and trust management of peers in mobile P2P network. The simulation results show that our model is highly robust and scalable in the dynamic environment of mobile networks.     

A multi-dimensional trust evaluation model for large-scale P2P computing

In large-scale peer-to-peer (P2P) computing, trust management technology has become a key requirement for network security. However, trust is one of the most complex concepts in network communities. It involves many factors, such as, assumptions, expectations, behaviors, risks, and so on. As a result, trustworthiness has multi-dimensional properties. In this paper, an innovative trust model is proposed for large-scale P2P computing, in which multiple factors are incorporated to reflect the complexity of trust. More importantly, the properties (weights) of these factors are dynamically assigned by weighted moving average and ordered weighted averaging (WMA-OWA) combination algorithms. This model surpasses the limitations of existing approaches, wherein weights are assigned subjectively. The simulation results show that, compared with the existing approaches, the proposed model provides greater accuracy and a more detailed analysis in trust evaluation.     

Exploring the antecedents of trust in virtual communities

Although previous research has established that interpersonal trust and system trust are critical in shaping individual behaviour in virtual settings, the two perspectives have not been examined by IS researchers in virtual communities (VCs) simultaneously. Drawing from prior literature on trust and VCs, a research model for understanding the importance of trust in members and trust in system and their antecedents in VCs is presented. Six trust-building factors were identified using three trust-building bases (calculative base, relationship base and technology base). Data were collected from 324 members of a technical VC to test the model. The study shows that trust in members and trust in system have significant influences on knowledge sharing intention. The study also indicates that knowledge growth, perceived responsiveness and shared vision affect trust in members positively, while knowledge quality influences trust in system significantly. The study discusses the theoretical and managerial implications of this study and proposes several future research directions.