项目名称: 移动社会网络中情境感知的多维个性化信任评价研究
项目编号: No.61502161
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 自动化技术、计算机技术
项目作者: 姜文君
作者单位: 湖南大学
项目金额: 21万元
中文摘要: 移动社会网络是一个或多个有着相同或相似兴趣的个体,通过移动设备来互相联络而形成的社会化网络。信任评价是网络与信息安全领域一种新的思想和方法,用于评估目标对象的信任程度,从而为下一步的交互决定提供指导。本项目提出移动社会网络中情境感知的多维个性化信任评价研究,主要是面向实际的复杂移动社会网络应用,利用社会网络分析和图算法等技术,从特定用户的角度,对其他用户的信任程度评估展开深入研究。主要研究如何收集多维信任证据,即信任相关的情境和主客观非情境信息;探讨用户观点相互影响的规律,理解信任证据发挥作用的原理和方式,指导信任模型的设计;扩展小世界网络理论构造高质量信任图,引入广义网络流来实施信任评价。相关工作是社会网络分析、移动计算和信任评价研究不断深化融合的一个交叉课题。通过这一系列创新性的系统研究,本项目将提出高效实用的信任模型和算法,能够为移动社会网络个性化信任评价提供有效的理论和技术支撑。
中文关键词: 移动社会网络;个性化信任评价;;多维信任证据;情境感知;小世界网络
英文摘要: Mobile social network (MSN) is a kind of social network where individuals with similar interests converse and connect with one another through their mobile devices. Trust evaluation is a new approach in the field of network and information security, which can estimate the target’s trustworthiness, and thus guide the decision-making for further interactions. This project focuses on the issues of context-aware multi-dimensional personalized trust evaluation in MSNs. More specifically, we target on the real complex MSN applications, borrow the techniques in social network analysis, graph algorithms, etc., to study the trust evaluation issues between any two users in MSNs. The detailed issues include collecting multi-dimensional trust evidence, including the trust-related context information and other subjective or objective non-context information; exploring the influence patterns of user opinions, so as to understand how the trust evidence takes effects and guide the design of trust models; generating high-quality trusted graph using small-world network theory and conducting trust evaluation using generalized network flow. This is a cross project derived from social network analysis, mobile computing, and trust evaluation. We will design practical and efficient mechanisms and algorithms for trust evaluation, which can provide the significant theoretical and technical supports to the personalized trust evaluation between nodes in the MSNs.
英文关键词: mobile social network;personalized trust evaluation;multi-dimensional trust evidence;context-awareness;small-world network