Feature-based Characterization and Clustering of Social Networks

Abstract

How do we distinguish one type of social networks from another if topologies are the only available information? In this thesis we proposed an approach to characterize social networks with techniques widely used in the social network analysis These features are computed only based on the given topologies With the aid of proposed characteristics classification can then be performed between different types of networks Our experiments show that a high accuracy can be achieved based on the proposed method The approach can be used for advertisement distribution system recommendation systems and DGA-based botnet detection systems Experiment also shows that the proposed system can be applied to anomaly detection system

Date of Award	2015 Aug 23
Original language	English
Supervisor	Hui-Tang Lin (Supervisor)