Prof. Rongxing Lu of University of New Brunswick

Abstract:  Similarity queries, giving a way to disease diagnosis based on similar patients, have wide applications in eHealthcare and are essentially demanded to be processed under fine-grained access policies due to the high sensitivity of healthcare data. One efficient and flexible way to implement such queries is to outsource healthcare data and the corresponding query services to a powerful cloud. Nevertheless, considering data privacy, healthcare data are usually outsourced in an encrypted form and required to be accessed in a privacy-preserving way. In the past years, many schemes have been proposed for privacy-preserving similarity queries. However, none of them is applicable to achieve data access control and access pattern privacy preservation. In this talk, we present an efficient and access pattern privacy-preserving similarity range query scheme with access control, which can well address the above challenges.

Biography:

Dr. Rongxing Lu is an associate professor of computer science at UNB. He was awarded the IEEE Fellow distinction in 2020. IEEE Fellow is the highest grade of membership and is recognized by the technical community as a prestigious honor and a significant achievement. The Fellow designation is conferred by the IEEE Board of Directors upon a person with an outstanding record of accomplishments in any of the IEEE fields of interest. The total number elevated in any one year cannot exceed one-tenth of one- percent of the total voting membership.

Dr. Lu has been a faculty member at UNB since 2016; he was previously an assistant professor at the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore (2013 to 2016). Dr. Lu worked as a postdoctoral fellow at the University of Waterloo from 2012 to 2013 after finishing his PhD there in 2012, for which he was awarded the prestigious Governor General’s Gold Medal. This was Dr. Lu’s second PhD, having previously received is first from the Shanghai Jiao Tong University, China, in 2006. Among other accolades, Dr. Lu won the 8th IEEE Communications Society Asia Pacific Outstanding Young Researcher Award in 2013.

Dr. Lu’s research interests include applied cryptography, privacy-enhancing technologies, and IoT-Big Data security and privacy. He is known for his early contribution to secure vehicular ad hoc networks, where he introduced the concept of efficient privacy preservation protocols in vehicular communications, enabling quick and efficient safety message authentication that protects the driver’s identity and location from the public, but still allows certain trusted authorities to trace the real identities of message senders in the event of disputes. Conditional privacy has since become a key design objective for secure and privacy-preserving protocols for vehicular communication. Dr. Lu has also contributed distinctively to the advancement of privacy-enhancing techniques in Internet of Things and Big Data, including in the areas of smart grid, eHealthcare, and cloud computing infrastructure.

Address:Faculty of Computer Science, University of New Brunswick, Fredericton, New Brunswick, Canada