Concordia University


CIISE Guest Lecture: Big Data and Privacy

Concordia Institute for Information Systems Engineering

Dr. Noman Mohammed,
McGill University

Date: Oct. 28 (10:30 am)
Location: EV3.309


Big data is the fuel of modern economy. It allows us to do better urban planning, combat new diseases, ensure national security, and has become the driving force behind innovation, productivity, and growth. All these new possibilities are enabled by new technologies that are capable of storing, integrating, and analyzing all sorts of digital breadcrumbs that we leave behind in this information age. On one hand, the collected data offers tremendous opportunities for mining useful information. On the other hand, the mining process poses a threat to individual privacy since the collected data often contains sensitive information. The current practice in data sharing relies primarily on policies and guidelines on the types of data that can be shared and agreements on the use of shared data. This approach alone may lead to excessive data distortion or insufficient protection. This talk will present the recent research results that try to find a right balance between the privacy protection and big data rewards. In particular, I will explain different definitions of privacy model, show their limitations, describe some algorithms to enforce them, and discuss open problems for future research.


Noman Mohammed is an NSERC postdoctoral fellow in the School of Computer Science at McGill University. Before coming to McGill, he was a member of the Cryptography, Security, & Privacy (CrySP) research group at the University of Waterloo. He received a Ph.D. degree in Computer Science from Concordia University in 2012. His research interests include privacy-preserving data sharing, secure distributed computing, trustworthy cloud computing, and wireless network security. He has received several prestigious awards including NSERC postdoctoral fellowship, Alexander Graham Bell Canada Graduate Scholarship (NSERC CGS), and the Best Student Paper Award in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2009.

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