基于簇的移动自组网络信任管理模型

对MANET的特点和它所面临的安全问题进行深入的分析和研究,指出设计合理的信任模型是MANET安全的首要问题。文中首先分析现有的MANET安全解决方案中的不足,进一步对MANET中的信任管理问题进行广泛的讨论。在此基础上提出基于簇的动态信任管理模型（Dtrust）。该模型有效地解决了MANET中的盲目信任问题,最后对该模型下簇的更新方法进行了描述。模拟实验证明了该模型的可行性。     

操作系统信任基建模的方法学研究

倡导操作系统在确立应用系统的可信性中具有不可或缺的作用之理念,以Web应用为聚焦点,诠释操作系统信任基(TBOS)的思想.以如何确保TBOS的可信性为主线,讨论TBOS建模的研究方法.提出由信任监控核心引擎、内核信任监控器和核外信任监控器三大部分组成的TBOS体系结构,提出发挥硬件效能与缩小软件尺寸相结合的研究方针,阐述TBOS建模中的关键问题和关键技术,从模型构造方法、信任监控方法、域间协同方法、隔离保护方法、硬件特性抽象方法和软件尺寸缩减方法等方面建立TBOS建模的方法学基础.     

基于回代信赖域的电阻层析成像算法

针对电阻层析成像(ERT)技术中反演问题的病态性,提出一种改进的回代信赖域算法BTR(Backtracking Trust Region),并将其应用于气/水两相流的可视化测量。该算法通过信赖域算法获得迭代方向,通过回代技术获得迭代步长,可在减小重建误差的同时,提高成像速度。利用Comsol软件进行仿真,并设计ERT系统对各种典型流型进行测量,验证了算法的可行性。通过与Landweber算法、共轭梯度算法和现存的信赖域算法的比较,证明本文方法明显改进了成像精度和实时性。     

Overview of the InterPARES Trust Project in Africa: Trusting Records in an Increasingly Networked Environment

InterPARES Trust (IP Trust) research project’s goal is to generate the theoretical and methodological frameworks that address issues related to the management of digital records in networked environments. Team Africa forms part of the IP Trust project and is undertaking six case studies. This article provides an overview of the research activities within each of the case studies. Team Africa’s case studies began recently and, therefore, there are no final products of the research process. Nonetheless, ongoing dissemination activities include three conference presentations (in Croatia, Spain, and the United States) as well as eight peer-reviewed articles published. Team Africa’s case studies focus on actionable factors defined from the ground up rather than from purely theoretical constructs. One case study’s output addresses trustworthiness of records in South Africa’s public audit processes. Three case studies’ output will address the management of digital records in Botswana, Kenya, and Zimbabwe. Another case study’s output addresses the legislative and regulatory provisions related to management of records in South Africa. The last case study’s output is geared to aligning the curriculum of professionals that manage records in Africa’s institutions of higher learning.     

Adoption of e-government services in Turkey

This research aims to investigate underlying factors that play role in citizens' decision to use e-government services in Turkey. UTAUT model which was enriched by introducing Trust of internet and Trust of government factors is used in the study. The model is evaluated through a survey conducted with Turkish citizens who are from different regions of the country. A total of 529 answers collected through purposive sampling and the responses were evaluated with the SEM (Structural Equation Modeling) technique. According to the results, Performance expectancy, Social influence, Facilitating conditions and Trust of Internet were found to have a positive effect on behavioral intention to use e-government services. Additionally, both Trust factors were found to have a positive influence on Performance expectancy of e-government services, a relation which, to our best knowledge, hasn't been tested before in e-government context. Effect of Effort expectancy and Trust of government were found insignificant on behavioral intention. We believe that the findings of this study will guide professionals and policy makers in improving and popularizing e-government services by revealing the citizen's priorities regarding e-government services in Turkey.     

A survey of trust in computer science and the Semantic Web

Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.     

支持向量机的中文文本分类研究

支持向量机是一种基于统计学习理论的新型机器学习方法,在文本分类领域取得了很好的效果。使用支持向量机进行了文本分类的研究,实现了一个中文文本自动分类系统,并给出了实验结果。     

可信计算环境构建机制研究进展

可信计算环境构建是通过软硬件结合的方式构建满足可信计算定义的系统,使其上进行的计算具有真实性、机密性、可控性等特性,并利用这些特性来弥补仅依靠传统安全防护方式的不足,从而更好地解决计算机安全面临的挑战和问题。介绍了可信计算环境构建的硬件基础,归纳了近年来基于静态可信度量根、动态可信度量根以及轻量虚拟机监控器的可信计算环境的构建机制,分析了现有可信计算环境构建机制的优势和不足;通过对可信计算环境中信任链的分析,指明了今后的研究方向。     

信任度评估模型在网上医院安全中的应用研究

信任管理是当前网格计算安全研究的热点。本文在介绍信任管理概念和概述信任度评估模型的基础上,根据信任评价的特点,提出了一个基于模糊理论信任度评估模型,结合国内某知名医院的网上医院,举例说明上述信任度评估模型在网上医院信任管理中的运用。     

信任度评估模型在网上医院安全中的应用研究

信任管理是当前网格计算安全研究的热点。本文在介绍信任管理概念和概迷信任度评估模型的基础上，根据信任评价的特点．提出了一个基于模糊理论信任度评估模型，结合国内某知名医院的网上医院，举例说明上述信任度评估模型在网上医院信任管理中的运用。     

A survey on Security Issues of Reputation Management Systems for Peer-to-Peer Networks

The objective of this paper is to present a comprehensive survey of security issues in Reputation based Trust Management system (RTMS) also known in short as Reputation Management Systems for P2P networks. The wide adoption of P2P computing has enhanced content publishing, pervasive information collection, streaming of real-time sensed data and information sharing on an enormous global scale. At the same time, the open and anonymous nature of P2P makes it vulnerable to malicious attacks and the spread of malware. In this paper, we discuss in detail the different security attacks on P2P systems and have categorized them as network-related and peer-related attacks. RTMS helps to establish and evaluate Trust, which is the degree of belief that is established to prove that the right user is accessing the right resource. We have explained the different Trust Management schemes used in P2P networks and have compared them on the basis of trust establishment, security features, trust evaluation and weakness. We have surveyed the RTMSs currently in use and have compared them on the basis of reputation collection, aggregation, computation, storage and degree of centralization of reputation computation and management. We also present a comparison of protection provided by RTMs against the various security attacks discussed. Open research issues and challenges that have yet to be addressed in the design of current RTMs have been presented in detail. This survey can be used as a reference guide to understand Trust Management and RTMS for P2P networks and to further research in RTMSs to make them efficient, reliable and scalable to enable and promote the utilization of P2P systems for large communities and applications.     

基于评价向量的P2P电子商务信任模型

针对现有P2P信任模型中交易因素考虑不全面、缺乏恶意节点识别机制而导致无法防御恶意节点共谋攻击和耗费网络带宽等问题,提出一种新的P2P信任模型EVTM,该模型采用向量化的方式表示评价的标准,引入时间衰减因子和惩罚机制,促使模型中交易节点积极地、正确地评价,从而构造一个诚信、可靠的交易环境。仿真实验进一步证明EVTM不仅可以根据用户的不同需求对交易对象做出更合理的信任评估,而且能有效地避免恶意节点的共谋攻击,从而降低交易的风险,减少损失。     

Projection Support Vector Machine Generators

Large-scale Support Vector Machine (SVM) classification is a very active research line in data mining. In recent years, several efficient SVM generation algorithms based on quadratic problems have been proposed, including: Successive OverRelaxation (SOR), Active Support Vector Machines (ASVM) and Lagrangian Support Vector Machines (LSVM). These algorithms have been used to solve classification problems with millions of points. ASVM is perhaps the fastest among them. This paper compares a new projection-based SVM algorithm with ASVM on a selection of real and synthetic data sets. The new algorithm seems competitive in terms of speed and testing accuracy.     

A systems ergonomics analysis of the Maidstone and Tunbridge Wells infection outbreaks

This paper describes a systems ergonomics analysis of the recent outbreaks of Clostridium difficile, which occurred over the period 2005–07 within the UK Maidstone and Tunbridge Wells NHS Trust. The analysis used documents related to the outbreak, alongside the construction of a system model in order to probe deeper into the nature of contributory factors within the Trust. The findings from the analysis demonstrate the value of looking further at cross-level and whole-system aspects of infection outbreaks. In particular, there is a need for further study of the causal relationships that exist between hospital management and clinical management levels within the system. Finally, the paper discusses ways forward and strategies that could be adopted in order to limit the outbreak of hospital-related infections and shape future research. The approach used for the system analysis described in the paper could be used by healthcare practitioners and ergonomists to probe deeper into the causes of infection outbreaks and to extend the scope of interventions aimed at preventing their occurrence.     

10月装机推荐配置

介绍了一个基于内容的维文文本检索系统,该系统采用向量空间模型.文中对该系统的设计思想进行了介绍,给出了文档标引、权值计算和相似度计算的具体方法,并针对维文自身的特点.对维文的存储以及维文文档特征项的抽取等方面的问题进行了具体探讨.     

一种多字体特大字符集字符识别系统

多字体特大字符集字符识别是当前OCR技术研究的热点之一。本文利用一组在抗干扰和描述字符拓扑结构方面具有互补性的特征,其于Support Vector技术和可增长自组织神经网络模型,建立一种识别系统来处理该问题。其中包括一个利用Supprt Vector技术建立的Optimal Margin语言分类器,一个以可增长自组织神经网的粗分类器,结合统计和结构两种识别方法的三级汉字分类器,最后给出良好的实验结果,从而得到该识别系统为解决上述问题的有效方法之一的结论。     

P2P网络信任模型的研究

介绍了当前P2P网络信任模型的分类,并归纳了当前国内外信任模型的研究现状,最后指出了今后P2P网络信任模型的发展应兼具安全性与可行性。     

基于关联向量机的混沌时间序列预测

混沌是一种貌似无规则的运动,指在确定的系统中,不需附加任何随机因素亦可出现类似随机的行为.在混沌的研究上,根据混沌系统提取的非线性时间序列对系统的未来进行预测,是一个十分重要的方面,混沌时间序列的非线性性给预测建模带来困难.关联向量机(RVM)是一种建立在支持向最机(SVW)之上的统计学习新方法.基于RVM埘以典型混沌时间序列为对象展开预测研究,实验表明在若干步内,RVM具有较高预测准确度,适用于混沌时间序列的多步预测.     

利用LS—SVM模块化决策系统求解EEG源参数

给定头皮脑电位的分布推算脑内电活动的源是脑电研究的一个重要的方面.研究涉及到信息科学、电磁场计算及生物医学工程等多个学科领域,其研究成果在神经疾病诊断、探索人的感觉和认知过程等方面具有蕈要意义.基于最小二乘支持向最机(LS-SVM)算法建立模块化决策系统,首先对脑电数据进行分类,然后依据分类结果提取数据样本,并建立回归模型,最后求解多种偶极子源参数.从而建立起头皮电压和脑电源参数之间的内在联系,为脑电动态分析提出一种实时的研究思路.计算机仿真计算结果证明了此方法的有效性.     

Understanding the effects of trust and risk on individual behavior toward social media platforms: A meta-analysis of the empirical evidence

Trust and risk have been theorized and empirically approved as the most influential factors affecting individual behavior toward social media platforms (SMPs). However, the evidence is scattered and the understanding of the effects is ambiguous. To address this problem, a rigorous and quantitative meta-analysis was conducted to investigate the empirical evidence of 43 studies in information systems research between 2006 and 2014. The findings suggested that trust and risk both had significant effects on individual behavior toward SMPs but that trust had a stronger effect. Moderating effects of trust objects (community members vs. platforms) and platform types (virtual communities vs. social networking sites) were found. Surprisingly, culture was found to exert no moderating effect. This paper contributes more generalized knowledge to social media research literature to the theory with regard to the influence of trust and risk on individual behavior toward SMPs. The knowledge serves as the foundation for future research efforts in social media. Implications for practice are discussed.