Prof. SM Yiu
Title: A balance between privacy and tracing anomalous cases – cryptographic solutions
Bio:
SM Yiu is currently a Professor in the Department of Computer Science of the University of Hong Kong and is an Associate Director of a newly established HKU-SCF FinTech Academy. He is also the
Director of the FinTech and Blockchain Laboratory, the Associate Director of the Center for Information Security and Cryptography (CISC) of the department. He was selected three times (2016, 2017, and 2019) by Clarivate Analytics as one of the highly cited researchers in Computer Science. He is also among the top 1% researchers in the University of Hong Kong for nine consecutive years (2011 – 2019). He has published 300 papers in refereed journals and conferences. His research areas include FinTech, security and cryptography, and bioinformatics. He was the conference/programme chair/co-chair of numerous conferences in these areas, including RECOMB, ISMB, which are among the top three flagship conferences in Bioinformatics, ASIACRYPT, which is one of the three flagship conferences in Cryptography. He is also one of the three representatives for Hong Kong in the steering committee of ASIACRYPT. He has been involved in research projects with major grants from the Government as the Principal Investigator or one of the Co-Principal Investigators. Besides fundamental research, Prof. Yiu is also a devoted teacher and has been selected for the teaching award recipient once from HKU, twice from the Faculty of Engineering and seven times from the Department.
Abstract:
Privacy is becoming a major concern. Many privacy leakage instances become news’ headlines. How to protect one’s privacy is, no doubt, an important issue: from a simple task such as filling an online questionnaire to recording one’s health information. On the other hand, there are also many examples that tracing the identities of entities are very critical as well. To name a few examples, tracing close-contact persons of a confirmed COVID-19 infected case, or tracing the money laundry paths of cryptocurrency. While we want to protect the privacy of all people who are innocent, it is also important to trace identities of anomalous cases. In this talk, we will discuss this problem and provide examples how cryptographic solutions can be used to strike a balance between the privacy issue and the tracing of suspicious cases for fighting virus and crime.
Prof. Shui Yu
Title: Big Data Privacy: from Networking and Artificial Intelligence Perspectives
Bio:
Shui Yu is a Professor of School of Computer Science, University of Technology Sydney, Australia. Dr Yu’s research interest includes Security and Privacy, Networking, Big Data, and Mathematical Modelling. He has published two monographs and edited two books, more than 300 technical papers, including top journals and top conferences, such as IEEE TPDS, TC, TIFS, TMC, TKDE, TETC, ToN, and INFOCOM. Dr Yu initiated the research field of networking for big data in 2013. His h-index is 45. He is currently serving a number of prestigious editorial boards, including IEEE Communications Surveys and Tutorials (Area Editor), IEEE Communications Magazine. He is a Senior Member of IEEE, a member of AAAS and ACM, and a Distinguished Lecturer of IEEE Communication Society.
Abstract:
Big data is revolution for our society. However, it also introduces a significant threat to our privacy. In this talk, we firstly present the essential issues of privacy preserving in the big data setting, then we review the current work of the field from two perspectives: networking and artificial intelligence. Then we discuss the challenges in the domain and possible promising directions. We humbly hope this talk will shed light for forthcoming researchers to explore the uncharted part of this promising land.