Fraud Analysis and Detection for Real-Time Messaging Communications on Social Networks

Liang-Chun CHEN  Chien-Lung HSU  Nai-Wei LO  Kuo-Hui YEH  Ping-Hsien LIN  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.10   pp.2267-2274
Publication Date: 2017/10/01
Publicized: 2017/07/21
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016INI0003
Type of Manuscript: INVITED PAPER (Special Section on Security, Privacy and Anonymity in Computation, Communication and Storage Systems)
Facebook,  fraud analysis,  latent semantic analysis,  natural language processing,  social networks,  

Full Text: FreePDF

With the successful development and rapid advancement of social networking technology, people tend to exchange and share information via online social networks, such as Facebook and LINE.Massive amounts of information are aggregated promptly and circulated quickly among people. However, with the enormous volume of human-interactions, various types of swindles via online social networks have been launched in recent years. Effectively detecting fraudulent activities on social networks has taken on increased importance, and is a topic of ongoing interest. In this paper, we develop a fraud analysis and detection system based on real-time messaging communications, which constitute one of the most common human-interacted services of online social networks. An integrated platform consisting of various text-mining techniques, such as natural language processing, matrix processing and content analysis via a latent semantic model, is proposed. In the system implementation, we first collect a series of fraud events, all of which happened in Taiwan, to construct analysis modules for detecting such fraud events. An Android-based application is then built for alert notification when dubious logs and fraud events happen.