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2013/12/02, MC103, 12 - 12:30

Applying Data Mining to Real-life Crime Investigation
Prof. Benjamin Fung , Associate Professor, McGill School of Information Studies

Abstract:

Data mining has demonstrated a lot of success in many domains, from direct marking to bioinformatics. Yet, limited research has been conducted to leverage the power of data mining in real-life crime investigation. In this presentation, I will discuss two data mining methods for crime investigation. The first method aims at identifying the true author of a given anonymous e-mail. The second method is a subject-based search engine that can help investigators to retrieve criminal information from a large collection of textual documents. If time permits, I will also provide an overivew of the ongoing and future research projects in the Data Mining and Security (DMaS) Lab.

Biography of Speaker:

Dr. Benjamin Fung is an Associate Professor of Information Studies (SIS) at McGill University and a Research Scientist in the National Cyber-Forensics and Training Alliance Canada (NCFTA Canada). He received a Ph.D. degree in computing science from Simon Fraser University in 2007. Dr. Fung collaborates closely with the national defense, law enforcement, and healthcare sectors. He has over 70 refereed publications that span across the prestigious research forums of data mining, privacy protection, cyber forensics, services computing, and building engineering. His data mining works in crime investigation and authorship analysis have been reported by media worldwide. Before pursuing his academic career, he worked at SAP Business Objects for four years. He is a licensed professional engineer in software engineering. Website: http://dmas.lab.mcgill.ca/fung