Research On Evaluation Method For Security And Trustworthiness Of Online Social Networks Platforms

Along with the rapid development of Internet technology,online social networking(OSN)platform has recently become more and more attention,with the convenient brought by open social media platform,there are also a lot of security(privacy)problem in the use process.The success of social networks relies on the level of trust between social group members and social network service providers.The security and trustworthiness of social platforms are the foundation of social interaction and are essential in information sharing and communication.Because there are many malicious sites,information spoofing and security issues in the social network platform,the traditional security and trust evaluation only focus on the trust and security of the users,and the evaluation and measurement method for the social media platform is not sound yet.Therefore,the purpose of this research propose a method of online social network platform security and trust measurement based on the signaling theory of management for the characteristics of online social network.The main contents of this paper are as follows:1.Online social network signal classification method based on signaling theory.Online social network platform of various types of property characteristics,information provided to users by platform operators,in the user and platform interaction,users of this kind of information and the manager of the platform are asymmetry,asymmetric information leads to the user can not accurately assess the trustworthiness of social networking platform.So this paper leads the signaling theory into the social media platform research.Firstly,the signal classification method is used to extract all kinds of signals that affect the users' use in the online social network platform,and the signals related to the platform security and trustworthiness are extracted according to the user survey questionnaire.Secondly,for the concept of the introduced signal,this paper uses the ontology description language to formalize such conceptual attributes,and uses the behavioral timing logic to describe the behavior of the signals in the platform.2.Multi-factor evaluation of the platform using the extracted data of the research content;the FAHP evaluation method was used to determine the weight of the various signals related to the security trustworthiness and the weighting was calculated.Use the crowd sourcing ideas and advantages to explore the social media infrastructure platform for the trustworthiness of the community assessment of measurement methods.Finally,an evaluation experiment is carried out on a realistic multimedia social networking platform(Cy VOD.net).Through the analysis of the characteristics of the real social platform,the task of group assessment is assigned,the platform enhancement and optimization scheme is proposed,and the program is validated by the research content,the integrity of the social platform evolution process is reflecting.The experimental results show that this method can accurately calculate the security value of the social platform and the evaluation value of the trust elements,which can further guide the social media network platform to realize the security and trust enhancement,so as to complete the functional evolution of the social platform.