报告人/Speaker: Dr. Tianqing Zhu（悉尼科技大学）
报告题目/Title: Differential Privacy in Cyber Physical Systems.
时间/Date & Time:2018年11月26日，9:00—10:00
With the development of Cyber Physical Systems, privacy issues in these systems become one of the most important topics in the past few years. It is worthwhile to apply differential privacy, one of the most influential privacy definitions, in cyber physical system to preserve privacy. However, as the essential idea of differential privacy is to release query results rather than entire datasets, a large volume of noise has to be introduced when a cyber-physical system releases large amounts of queries to its clients. In addition, it is almost impossible for a system to predict what type of queries a client may ask. Those two disadvantages hinder the application of differential privacy in cyber physical systems, such as Internet of Things and fog computing. To provide high quality services in the constraint of differential privacy, two challenges need to be tackled: one is how to decrease the correlation between large sets of queries, while the other is how to predict on newly entered queries. We transfer the data publishing problem in cyber physical systems to a machine learning problem, in which a prediction model will be shared with clients. The predict model is used to answer current submitted queries and predict results for newly entered queries from the public. Compared with the traditional method, the proposed prediction model enhances the accuracy of query results and consume limited privacy budget.
报告人简介/About the speaker:
Dr. Tianqing Zhu received her BEng and MEng degrees from Wuhan University, China, in 2000 and 2004, respectively, and a PhD degree from Deakin University in Computer Science, Australia, in 2014. Dr Tianqing Zhu is currently a senior lecturer in the school of software in University of Technology Sydney, Australia. Before that, she was a lecture in the School of Information Technology, Deakin University, Australia, from 2014 to 2018. Her research interests include privacy preserving, data mining and network security.