• De-anonymizing Social Network Neighborhoods Using Auxiliary and Semantic Information

      Morgan, Steven Michael; Novillo, Jorge; Adviser; Andriamanalimanana, Bruno; Reviewer; Reale, Michael; Reviewer (2015-12-11)
      The increasing popularity of social networks and their progressively more robust uses provides an interesting intersection of data. Social graphs have been rigorously studied for de-anonymization. Users of social networks will provide feedback to pages of interest and will create a vibrant profile. In addition to user interests, textual analysis provides another feature set for users. The user profile can be viewed as a classical relational dataset in conjunction with graph data. This paper uses semantic information to improve the accuracy of de-anonymizing social network data.