Towards Social Engineering: Research On Analysis And Mining Of Social Networking Services

With the rise of Web2.0, there have been lots of network applications on internet,while SNS (Social Network Service) has becoming extremely popular one of them foronline communication and collaboration. From SNS, users could not only share orabsorb knowledge, but also take the risk of social engineering attacks themselves.This paper proposes a new method towards social engineering to support analysisand mining of SNS users’ privacy. This social engineering based method resolves theproblem of collecting datasets from multi-source. In order to analyze and mineprivacy of SNS user, the method also combines three technologies: topic model, socialrelationships and visualization. The study can be used to help SNS websites shapeusers’ privacy privacy-protection strategy, and will have great significance inimproving the security of SNS.In this paper, we first analyze the related work about Social Network Analysis(SNA) and Social Engineering, and then research three key technologies of analysisand mining of SNS:1) Multi-source data collection. In order to collect SNS data frommultiple platforms in real time, this paper analyzes the default privacy policy of somefamous SNS sites, and a historical social activity data based task scheduling algorithmwhich can assure SNS data collected in real time is also proposed.2) A method ofSNS topic models extraction based on self-adaptively LDA (Latent DirichletAllocation) modeling. The paper presents a new evaluation metric for topic modelsextraction from SNS dataset. Then, by combining LDA modeling with this new metric,a LDA modeling method is proposed which can determine the topic number of LDAself-adaptively.3) Research on the approach of privacy mining. Based on the theoryof social network, the paper also provides the suggestions of mining approach byestablishing weak links to target.Then, based on the key technologies proposed above, we have designed and developed a platform of privacy analysis and mining for some research laboratory.The specific requirements and the architecture have been analyzed in detail usingUML including use-case model, logical model, etc. This platform has beenimplemented using MySql、J2EE、JGibbLDA and Restful Web Service.At last, we discuss the experiments about key technologies proposed in this paper.Experiments were successfully performed, and the results show that all of them havepassed the function and performance testing. Now, the platform has been tried out inthe laboratory’s daily business, and it can satisfy laboratory’s requirements well.