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开放计算系统中基于DSmT的信任管理研究

作　者: 王进
导　师: 孙怀江
学　校: 南京理工大学
专　业: 模式识别与智能系统
关键词: Trust management Dezert-Smarandache Theory Subjective logic Trust representation Reputation Transitivity Second-hand evidence Recommender system
分类号: TP393.08
类　型: 博士论文
年　份: 2009年
下　载: 122次
引　用: 2次
阅　读: 论文下载

内容摘要

Open computational systems, such as e-business, peer-to-peer networks and grid, are becoming the main trends. Open computational systems are characterized as both open and dynamic. The interacting parties may be strange and selfish members, which brings great risks to the interactions. The traditional secure mechanisms depend mainly on the authority center which is difficult to establish in open computational systems, so it is no longer sufficient for the open computational systems. Trust management inspired by the trust mechanisms in society is an important research of social computing. Trust management is trying to build up similar trust mechanisms in open computational systems, which is considered a promising way to solve the trust problem in open computational systems.From the point of view of trust representation, this dissertation researched trust management based on DSmT, including trust representation, acquisition, transitivity, accumulation, decision, malicious behavior resistance, second-hand trust evaluation modification and application to recommender systems. This study mainly has four contributes:(1) DSmTrust, a trust model based on DSmT, is provided in order to handle the common problem of insufficient trust representation in open computational systems. Besides DSmTrust, further problems including trust acquirement, trust decision and malicious behavior resistance are studied. Simulations show the efficiency and effectiveness by comparisons.(2) The DSmT Subjective Logic which is an extension of the Subjective Logic is presented. The discounting operator and consensus operator are applied to trust transitivity and trust accumulation of DSmTrust, respectively. The flexibility of discounting operator and the rationality of consensus operator are proved by experiments and examples.(3) A disturbing model is presented to modify the second-hand trust evaluations because of the problem of inaccurate second-hand information in trust management. This disturbing model is reduced to the inverse problem of DSmT. The simulations indicate that the disturbing model can explain and modify well the difference between the second-hand trust evaluations and the first-hand trust evaluations.(4) DSmTrust is preliminarily applied to recommender systems. The constraint of common ratings in collaborative filtering is relieved in DSmTrust by trust transitivity. The preliminary results show that DSmTrust can effectively handle the sparse problem and cold start problem comparing with traditional collaborative filtering, and the recommendation precision of DSmTrust is better than Massa’s approach.This dissertation applies DSmT to trust management. On the one hand, this work provides a novel approach to represent and handle trust for the field of trust management and it can be a support of the future interoperable trust model for the heterogeneous trust models. On the other hand, this study which is a paradigm for the application of DSmT will drive the development of DSmT.

全文目录

Abstract  5-8
1 绪论  8-20
  1.1 课题背景及研究意义  8-11
  1.2 研究现状和相关问题  11-16
  1.3 研究思路  16-18
  1.4 本文主要工作内容和创新成果  18-19
  1.5 本文的组织结构  19-20
2 开放计算系统中的信任  20-32
  2.1 信任的定义  20-21
  2.2 信任的特点  21-22
  2.3 信任的分类  22-23
  2.4 信任系统的分类  23-29
  2.5 信任相关概念  29-30
  2.6 本章小结  30-32
3 DSmTrust信任模型及相关研究  32-56
  3.1 证据理论信任模型相关工作  32-34
  3.2 DSmT  34-36
  3.3 DSmTrust信任表示  36-38
  3.4 DSmTrust信任获取  38-40
  3.5 DSmTrust信任决策  40
  3.6 抵御恶意行为  40-41
  3.7 实验:对比1(声誉的建立)  41-46
  3.8 实验:对比2(交互效率)  46-50
  3.9 实验:信任决策  50-53
  3.10 实验:恶意行为的抵御  53-55
  3.11 本章小结  55-56
4 DSmT主观逻辑  56-74
  4.1 Jφsang主观逻辑  56-59
  4.2 DSmT主观逻辑  59-65
  4.3 DSmTrust信任传递  65-71
    4.3.1 信任传递的分析  65-68
    4.3.2 实验:信任的传递  68-71
  4.4 DSmTrust信任聚合  71-72
  4.5 本章小结  72-74
5 DSmT反问题及其在专家推荐模型中的应用  74-83
  5.1 DSmT相关证据模型  74-76
  5.2 DSmT反问题  76-77
  5.3 DSmT反问题的近似求解  77-80
  5.4 一种基于DSmTrust的专家推荐模型  80-82
    5.4.1 扰动模型  80-81
    5.4.2 场景  81
    5.4.3 实验结果与分析  81-82
  5.5 本章小结  82-83
6 DSmTrust信任模型在推荐系统中的应用研究  83-99
  6.1 推荐系统中的信任管理  83-91
    6.1.1 推荐系统  83-85
    6.1.2 推荐系统的分类  85-87
    6.1.3 问题的提出与意义  87-88
    6.1.4 信任在推荐系统中的应用研究现状  88-90
    6.1.5 常用数据集  90-91
  6.2 DSmTrust信任模型在推荐系统中的应用  91-92
    6.2.1 集中式DSmTrust方法  91-92
    6.2.2 分布式DSmTrust方法  92
  6.3 实验与分析  92-97
    6.3.1 指标  93
    6.3.2 实验  93-97
  6.4 本章小结  97-99
7 结论与展望  99-102
  7.1 结论  99-100
  7.2 展望  100-102
致谢  102-103
参考文献  103-112
附录  112

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