在线社交网络平台安全性和可信度评估度量方法研究

发布时间：2018-06-05 01:23

本文选题：社交媒体网络 + 信号理论　；参考：《河南科技大学》2017年硕士论文

【摘要】：随着互联网技术的迅猛发展,在线社交网络(OSN)平台正在成为人类社会关系维系和信息传播的重要渠道和载体,开放的社交网络平台给用户带来使用便捷的同时,在使用过程中也引发了大量的安全(和隐私)问题。社交网络的成功依赖于社交群组成员彼此之间以及与社交网络服务提供商之间的信任程度。社交平台的安全性和可信度作为社会交互的基础,在信息共享与交流中至关重要。由于在社交网络平台中也存在不少恶意站点、信息欺骗和安全性等问题,但传统的安全和信任评估仅关注于用户间的信任关系和安全实现,而针对社交网络平台的评估和度量方法还不健全。因此,本课题的研究旨在针对在线社交网络特点,提出一种基于管理学信号理论的在线社交网络平台安全和信任度量方法。本文的主要研究内容如下:1.基于信号理论的在线社交网络信号分类方法。在线社交网络平台的各类属性特点,平台运营商提供给用户的信息等,在用户与平台的交互中,用户对这类信息的掌握与平台管理者之间出现了不对称性,信息的不对称性导致用户无法准确评估社交网络平台的可信度。因此本文将信号理论(Signaling Theory)引入到在线社交网络平台研究中。首先利用信号理论研究中对信号的分类方法,提取在线社交网络平台中影响用户的各类信号,并根据用户调研问卷,提取出与平台安全性和可信度相关信号。其次对于引入的信号概念,本文利用本体描述语言对此类概念属性进行形式化,利用行为时序逻辑对信号在平台执行行为进行行为描述。2.利用研究内容一提取的信号对平台进行多因素评价;使用FAHP评估方法确定各类与安全性可信度相关信号的指标权重并进行权重计算。利用众包思想和优势,探索在线社交网络平台安全性可信度的群体评估度量方法。最后,在一个现实的多媒体社交网络平台(Cy VOD.net)上进行了评估实验。通过现实社交平台特性分析,分配群体评估任务,将信号动、静态交互应用在群体评估环境设置中,提出平台增强与优化方案,利用研究内容一提出的方案进行实验验证分析,体现完整的社交平台进化过程。实验结果显示,该方法能够准确地计算社交平台的各安全和信任要素的评估值,可进一步指导社交网络平台实现安全和信任增强,从而完成社交平台的功能进化。
[Abstract]:With the rapid development of Internet technology, the online social network (OSN) platform is becoming an important channel and carrier for the maintenance of human social relations and the dissemination of information. The open social network platform brings convenience to users at the same time. There are also a lot of security (and privacy) problems in the process of use. The success of social networks depends on the level of trust that social group members have with each other and with social network service providers. As the foundation of social interaction, the security and credibility of social platform is very important in information sharing and communication. There are many malicious sites, information spoofing and security problems in the social network platform, but the traditional security and trust evaluation only focuses on the trust relationship and security implementation between users. However, the evaluation and measurement methods for social network platform are not perfect. Therefore, according to the characteristics of online social network, this paper proposes a method of online social network platform security and trust measurement based on management signal theory. The main contents of this paper are as follows: 1. A signal Classification method based on signal Theory for online Social Networks. Various attributes of online social network platform, information provided by platform operators, etc., in the interaction between users and platforms, there is asymmetry between users' mastery of such information and platform managers. Because of the asymmetry of information, users can not accurately evaluate the credibility of the social network platform. In this paper, signaling theory is introduced into the research of online social network platform. Firstly, using the signal classification method in the research of signal theory, we extract all kinds of signals that affect users in the online social network platform, and extract the signals related to the platform security and credibility according to the user survey questionnaire. Secondly, this paper uses ontology description language to formalize the concept attributes, and uses behavioral temporal logic to describe the behavior of signal execution on the platform. The platform is evaluated by using the signal extracted from the research content, and the index weights of various kinds of signals related to the reliability of security are determined by using the FAHP evaluation method and the weights are calculated. By using crowdsourcing idea and advantage, this paper explores a group evaluation method of online social network platform security reliability. Finally, an evaluation experiment is carried out on a real multimedia social network platform, Cy VOD.net. Through the analysis of the characteristics of the real social platform, the task of group evaluation is assigned, the signal dynamic and static interaction is applied to the setting of the group evaluation environment, the platform enhancement and optimization scheme is put forward, and the experimental verification analysis is carried out by using the scheme proposed in the first research content. Reflects the complete evolution of the social platform process. The experimental results show that this method can accurately calculate the evaluation values of the security and trust elements of the social platform, and can further guide the social network platform to achieve security and trust enhancement, thus completing the functional evolution of the social platform.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.08

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