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More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence

September 23, 2020 @ 11:00 am - 12:00 pm AEST

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By Professor Wanlei ZhouSchool of Computer Science, University of Technology Sydney, Australia

Artificial Intelligence (AI) has attracted a great deal of attention in recent years. However, alongside all its advancements, problems have also emerged, such as privacy violations, security issues and model fairness, etc. For example, adversarial samples can fool machine learning models, leading to incorrect results; Multi-agent systems may receive false information from malicious agents. As a result, many researchers have been exploring new and existing security and privacy tools to tackle these new emerging problems, and differential privacy is one of these tools. The key idea of differential privacy is to introduce calibrated randomization to the aggregate output, leading to several attractive properties, including Preserving privacy, Stability, Security, Fairness, and Composition, that can benefit some AI algorithms. In this talk, we show that differential privacy can do more than just privacy preservation. It can also be used to improve security, stabilize learning, build fair models, and impose composition in selected areas of AI. With a focus on regular machine learning, distributed machine learning, deep learning, and multi-agent systems, the purpose of this talk is to deliver a new view on many possibilities for improving AI performance with differential privacy techniques. Most of the content of this talk is based on the following papers:

  1. https://www.computer.org/csdl/journal/tk/5555/01/09158374/1m1eAPbg4JW
  2. https://ieeexplore.ieee.org/document/8685696
  3. https://www.computer.org/csdl/journal/tk/5555/01/09117188/1kGfwTyLZbq
  4. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9167262

Biography

Professor Wanlei Zhou is currently the Head of the School of Computer Science at the University of Technology Sydney (UTS), Australia. He received the B.Eng and M.Eng degrees from Harbin Institute of Technology, Harbin, China in 1982 and 1984, respectively, and the Ph.D. degree from The Australian National University, Canberra, Australia, in 1991, all in Computer Science and Engineering. He also received a DSc degree (a higher Doctorate degree) from Deakin University in 2002. Before joining UTS, Professor Zhou held the positions of Alfred Deakin Professor, Chair of Information Technology, and Associate Dean (International Research Engagement) of Faculty of Science, Engineering and Built Environment, Deakin University. Professor Zhou has been the Head of the School of Information Technology twice (Jan 2002-Apr 2006 and Jan 2009-Jan 2015) and Associate Dean of the Faculty of Science and Technology in Deakin University (May 2006-Dec 2008). Professor Zhou also served as a lecturer in the University of Electronic Science and Technology of China, a system programmer in HP at Massachusetts, USA; a lecturer in Monash University, Melbourne, Australia; and a lecturer in the National University of Singapore, Singapore. His research interests include security and privacy, parallel and distributed systems, and e-learning. Professor Zhou has published more than 400 papers in refereed international journals and refereed international conferences proceedings, including many articles in IEEE transactions and journals.

Zoom meeting

Meeting link: https://deakin.zoom.us/j/91751668822?pwd=WVAyc2VseURNQkw4VzdSQWZtZnprQT09

Phone one-tap: Australia: +61861193900,,91751668822#<tel:+61861193900,,91751668822>

Meeting ID: 917 5166 8822  Passcode: 707836

Skype for Business (Lync)  https://deakin.zoom.us/skype/91751668822

Venue

Online

Organiser

IEEE SMC Victorian Chapter