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.     

开放网格环境下动态信任模型研究

随着大规模分布式系统研究的深入,开放网络环境下的动态信任管理成为一个突出问题,通过分析动态环境信任关系的特点,借助模糊逻辑知识,给出了一个分布环境的动态信任评估模型。该模型充分考虑了信任的模糊性与主观性,运用模糊逻辑的方法来得到结点的直接信任值,同时对动态环境下全局信誉的迭代计算,通过增加推荐结点信息表来控制其计算效率。     

面向信任的协同模型*

针对开放分布式系统中收集实体的经验值和度量信任困难的现状,采用关注分离的原则,将实体的信任处理行为与计算行为、交互行为进行分离,提出了一个面向信任的协同模型。通过模型中的信任角色实时监听所绑定的计算实体的消息来更新经验值,进而计算信任度,为系统选择相对可信的计算实体提供了依据。最后,利用Java消息服务技术和EJB技术给出了该模型的实现框架。     

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 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.     

一种边缘设备动态信任度的评估模型

面向边缘计算环境中设备信任度评估的准确性和时间开销等问题,提出一种边缘设备动态信任度评估模型—D T EM.首先,利用时间退化因子表达直接信任度时效性,引入满意度函数修正贝叶斯方程,并结合激励机制评估边缘设备间的直接信任度.其次,利用改进的灰关联分析法确定指标权重,解决了间接信任度评估过程中推荐设备权重的问题.最后,通...     

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     

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.     

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.     

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.     

GenTrust: A genetic trust management model for peer-to-peer systems

In recent years, peer-to-peer systems have attracted significant interest by offering diverse and easily accessible sharing environments to users. However, this flexibility of P2P systems introduces security vulnerabilities. Peers often interact with unknown or unfamiliar peers and become vulnerable to a wide variety of attacks. Therefore, having a robust trust management model is critical for such open environments in order to exclude unreliable peers from the system. In this study, a new trust model for peer-to-peer networks called GenTrust is proposed. GenTrust has evolved by using genetic programming. In this model, a peer calculates the trustworthiness of another peer based on the features extracted from past interactions and the recommendations. Since the proposed model does not rely on any central authority or global trust values, it suits the decentralized nature of P2P networks. Moreover, the experimental results show that the model is very effective against various attackers, namely individual, collaborative, and pseudospoofing attackers. An analysis on features is also carried out in order to explore their effects on the results. This is the first study which investigates the use of genetic programming on trust management.     

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.     

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。     

一种综合的P2P网络信任模型

安全有效的信任模型是保证P2P 系统高效、稳定的关键技术之一。介绍一种适用于P2P 网络的综合信任模型,它参考了社会网络中信任关系的建立方法,从两个角度来计算节点的综合可信度。该模型中引入了非对称加密等安全机制,通过分析与仿真证明该模型能有效地抑制冒名和诋毁等非法行为,具有较强的安全性。     

一种服务多维信任属性模型的研究

随着Web服务研究的不断深入,从服务角色的角度出发考虑服务结构已经成为研究的热点问题。主要从服务的使用者、提供者和服务本身三个方面考虑,提出一个服务信任管理模型,通过使用者对服务信任属性的反馈信息修正提供者发布的服务主观信任信息,通过服务组装过程中获得的信任信息修正提供者提供的服务客观信任信息,从而为用户提供更加准确的基于信任的服务推荐。     

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.     

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 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.     

开放分布系统中局部信任度计算方法研究*

针对现有的局部信任度计算方法忽视了交互经验的时效性及充分性等问题, 提出一种证据理论框架下的局部信任度计算方法, 该方法采用了时效因子计算函数来区分不同时间内的交互经验在局部信任度计算中的重要性;同时,采用了半梯形函数来区分基于不同交互经验计算得到的局部信任度的有效性。实验分析表明,该方法对实体行为改变有较强的敏感性,能有效地降低对各种恶意实体的局部信任度。