10 citations · 62 across the 25 of their papers we have counts for
4 papers · 1 filter
Catching Loosely Synchronized Behavior in Face of Camouflage
Yikun Ban, Jiao Sun, Xin Liu
Fraud has severely detrimental impacts on the business of social networks and other online applications. A user can become a fake celebrity by purchasing "zombie followers" on Twit…
On Finding Dense Subgraphs in Bipartite Graphs: Linear Algorithms
Yikun Ban
Detecting dense subgraphs from large graphs is a core component in many applications, ranging from social networks mining, bioinformatics. In this paper, we focus on mining dense s…
No Place to Hide: Catching Fraudulent Entities in Tensors
Yikun Ban, Xin Liu, Yitao Duan +2
Many approaches focus on detecting dense blocks in the tensor of multimodal data to prevent fraudulent entities (e.g., accounts, links) from retweet boosting, hashtag hijacking, li…
BadLink: Combining Graph and Information-Theoretical Features for Online Fraud Group Detection
Yikun Ban, Xin Liu, Tianyi Zhang +4
Frauds severely hurt many kinds of Internet businesses. Group-based fraud detection is a popular methodology to catch fraudsters who unavoidably exhibit synchronized behaviors. We…