Data Deduplication Techniques in the Cloud

Day & Time: Monday, June 29, 2020
1:00 p.m. – 2:00 p.m.

Speaker: Dr. Fatema Rashid

Organizers: IEEE Toronto WIE

Location: Virtual – Zoom

Contact: Ayda Naserialiabadi

Abstract: Data security has become an integral part of today’s digital market. With the advent of cloud computing and influx of online services, privacy of the users has become a challenge for the service providers. With a tremendous increase in the number of privacy breeches all over the world, privacy preserving strategies for the data in the cloud have been studies in greater depths. To address security issues of the data in the cloud, privacy preserving techniques can be sub branched into Encryption, Differential Privacy and De-Identification. This talk covers the research done in all the three areas in order to preserve the privacy of the data from the cloud service provider or the third party mining the data. Encryption scheme can further be utilized to provide Data Deduplication strategy for the data in the cloud by keeping only one single copy of the identical data coming from different users. This will save digital space and at the same time provide data security to the users. The sharing of images and videos has made the multimedia data to become a huge portion of the data in the cloud. This talks covers de- duplication strategies applied to multimedia data in the cloud.

Registration: Please visit https://events.vtools.ieee.org/m/233946 to register.

Biography: Fatema Rashid completed her Bachelor of Science (BS) in Computer Science from National University of Computer and Emerging Sciences, Karachi, Pakistan in 2004. She completed her Master of Science (MS), Computer Science from Ryerson University, Toronto in 2009 with the thesis entitled   “Inverse Biometrics for Keystroke Dynamics”. Her PhD was completed in 2015 from Ryerson University and the title of the thesis was “ Secure Data Deduplication in Cloud Environments”.  She has the honour of being the first PhD of the Department of Computer Science at Ryerson University. She has published several publications with reputable journals like Journal of Information Security and Applications and conferences like IEEE Intl. Conference on BigData Computing Service and Applications

IEEE World Congress on Services, Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Symposium on Cyberspace Safety and Security, IEEE

Privacy, and Security and Trust (PST). She has also contributed a chapter for the book entitled “Guide to Big Data Applications by Springer”.  She has worked as Information Management Specialist at iG2 Inc., Toronto.  During this period, she contributed  3 white papers for the firm entitled “Interconnected Vulnerability, IoT and Next Generation Protection” , “A framework for Inside Threat Vulnerability Assessment “ and “Cloud Security and IoT Security Foundations ”.  She is currently involved as a Post Doctoral research fellow at Ryerson University and doing research in the area of Big Data Security with Differential Privacy and Generative Adversial Networks. She is a member of iCasL Center at Ryerson University and involved in different projects of cyber security, Big Data Security and Block Chain Security. She has a vast teaching experience of more than 5 years ranging from teaching as a lecturer in NUST, Pakistan, Ryerson University, Chang School of Continuing Education and Centennial College, Toronto.  During her education, she has been awarded Queen Elizabeth II Graduate Scholarship in Science and Technology two times at Ryerson University.