Data Mining for Privacy Protection, Authorship Analysis, and Reverse Engineering

Benjamin Fung - School of Information Studies, McGill University

Jan. 27, 2017, 2:30 p.m. - Jan. 27, 2017, 3:30 p.m.

Mc012 2:30pm

The objective of this presentation is to provide an overview of the research work conducted in the Data Mining and Security (DMaS) Lab at McGill University. We will discuss three research topics. (1) Privacy-preserving data mining: Since data mining often involves person-specific and sensitive information, the public has acquired the negative impression that data mining is a tool for intrusion on their privacy. Privacy-preserving data mining is a study of eliminating threats to privacy while preserving useful information in the released data. (2) Authorship analysis: Given an anonyous e-mail or some tweets, can we identify the author based on the writing styles? I will give a demonstration on an authorship analysis tool developed by DMaS. (3) Assembly code mining: Assembly code analysis is one of the critical processes for mitigating the exponentially increasing threats from malicious software. However, it is a manually intensive and time-consuming process even for experienced reverse engineers. An effective and efficient assembly code clone search engine can greatly reduce the effort of this process. We have implemented an award winning assembly clone search engine called Kam1n0. It is the first clone search engine that can efficiently identify a given query assembly function's subgraph clones from a large assembly code repository. I will give a live demonstration of Kam1n0.

Dr. Benjamin Fung is a Canada Research Chair in Data Mining for Cybersecurity, an Associate Professor of Information Studies (SIS), an Associate Member of Computer Science (SoCS) at McGill University, a Co-curator of Cybersecurity in the World Economic Forum (WEF), and a Research Scientist in the National Cyber-Forensics and Training Alliance Canada (NCFTA Canada). Collaborating closely with the national defense, law enforcement, transportation, and healthcare sectors, he has over 100 refereed publications that span across the 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 joining McGill, he was an Assistant/Associate Professor at Concordia University, and a system software developer at SAP Business Objects in Canada. Dr. Fung is a licensed professional engineer in software engineering. See his research website for more information.