CCECE 2021 Keynote Speech - Federated Learning and its applications to Internet of Things
As the Internet-of-Things devices are being widely adopted in all fields, such as smart houses, healthcare, and transportation, large amounts of data are being collected, shared, and processed. This fact raises many challenges on how to make the best use of this huge amount of data to improve the IoT systems’ security using artificial intelligence, taking into consideration the resource limitations in IoT devices and issues regarding data privacy. Different techniques have been studied and developed throughout the years. For example, Federated Learning (FL), which is an emerging learning technique that is very well known for preserving and respecting the privacy of the collaborating clients’ data during model training. The concepts of FL and Hierarchical Federated Learning (HFL) are evaluated and compared with respect of detection accuracy and speed of convergence, through simulating an Intrusion Detection System for Internet-of-Things applications. Different kinds of datasets (e.g., NSL-KDD) are used in our work to prove that our developed schemes are superior compared to other schemes in terms of training loss, testing accuracy, and speed of convergence. HFL also showed its efficiency over FL in reducing the effect of the non-identically and independently distributed data on the collaborative learning process.
In this Keynote, we review the current efforts by experts around the world to mitigate some of these challenges. Then, we showcase our research activities to contribute to these efforts and advocate possible solutions using AI and other tools. We provide ways on how to manage the available resources intelligently and efficiently in order to offer better conditions and provide improved services. Finally, we discuss some of our research results to support a variety of applications including how to secure these devices for successful healthcare service delivery in different aspects.
Speaker: Mohsen Guizani, Professor and IEEE Fellow; Senior EiC, IEEE Network
Date and Time
- Date: 16 Sep 2021
- Time: 09:00 AM to 10:00 AM
- All times are Canada/Eastern
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Zoom platform link https://zoom.us/j/96393792197
All registrants will be sent an email the day prior as a reminder with the link.
- Co-sponsored by Canadian Conference on Electrical and Computer Engineering (CCECE) 2021
- Starts 22 August 2021 04:26 PM
- Ends 16 September 2021 09:10 AM
- All times are Canada/Eastern
- No Admission Charge
Dr. Mohsen Guizani of Qatar University
Mohsen Guizani (S’85–M’89–SM’99–F’09) received the B.S. (with distinction), M.S. and Ph.D. degrees in Electrical and Computer engineering from Syracuse University, Syracuse, NY, USA. He is currently a Professor at the Computer Science & Engineering Department in Qatar University, Qatar. Previously, he worked in different institutions: University of Idaho, Western Michigan University, University of West Florida, University of Missouri-Kansas City, University of Colorado-Boulder, and Syracuse University. His research interests include wireless communications and mobile computing, applied machine learning, cloud computing, security and its application to healthcare systems. He was elevated to the IEEE Fellow in 2009. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science in 2019 and 2020. Dr. Guizani has won several research awards including the “2015 IEEE Communications Society Best Survey Paper Award” as well 4 Best Paper Awards from ICC and Globecom Conferences. He is the author of nine books and more than 800 publications. He is also the recipient of the 2017 IEEE Communications Society Wireless Technical Committee (WTC) Recognition Award, the 2018 AdHoc Technical Committee Recognition Award, and the 2019 IEEE Communications and Information Security Technical Recognition (CISTC) Award. He served as the Editor-in-Chief of IEEE Network and is currently serves on the Editorial Boards of many IEEE journals/Transactions. He was the Chair of the IEEE Communications Society Wireless Technical Committee and the Chair of the TAOS Technical Committee. He served as the IEEE Computer Society Distinguished Speaker and is currently the IEEE ComSoc Distinguished Lecturer.