Our paper “PrivDPR: Synthetic Graph Publishing with Deep PageRank under Differential Privacy” is accepted by SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). Congratulations to Sen!
On 21 Nov, Prof. Yang Xiang from Swinburne University of Technology, Australia will give a talk with title “Securing AI Systems: from Development to Deployment” in Distingsuihed Lecture Series on Research Centre for Privacy and Security Technologies in Future Smart Systems. The following link will be the recorded video of this talk.
Our paper “Federated Heavy Hitter Analytics with Local Differential Privacy” is accepted by International Conference of Management of Data (SIGMOD 2025)”. Congratulations to Yuemin! Our paper “Membership Inference Attacks and Defenses in Federated Learning: A Survey” is accepted by ACM Computing Surveys. Congratulations to Li!
Prof. Hu has been awarded an ITF grant with project title “MyGPTShield: A Personalized Privacy-Preserving Prompt Service for Large Generative AI Models”. The total amount is HK$2,000,010.
Prof. Hu has been awarded an RGC/GRF grant with project title “Right To Be Forgotten Made Easy: Machine Unlearning, Differential Privacy and Beyond”. The total amount is HK$1,038,967. Dr. Ye has been awarded an RGC/ECS grant with project title “Harnessing Sensitive Statistics from the Crowd: Towards Scalable Private Federated Analytics”. The total amount is HK$992,994.
Thanks to the outstanding rating of her research grant proposal in the Early Career Scheme, Dr. Ye Qingqing has received the Early Career Award from UGC this year. Every year, there are only 7-8 awardees in all 8 public universities in Hong Kong.
Our paper “PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy” has been accepted by International Conference on Very Large Databases (VLDB 2024).
The following papers from ASTAPLE current and former members are accepted by IEEE International Conference on Data Engineering (ICDE ’24), Utrecht, Netherlands, May 2024 as full research papers. Congratulations to all authors!
Our papers “LDPTube: Theoretical Utility Benchmark and Enhancement for LDP Mechanisms in High-dimensional Space”, “LDPGuard: Defenses against Data Poisoning Attacks to Local Differential Privacy Protocols”, and “EPS: Privacy Preserving Set-Valued Data Analysis in the Shuffle Model” have been accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
Our paper “DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release” has been accepted by PVLDB 2024. Our papers “LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy” and “FRESH: Towards Efficient Graph Queries in an Outsourced Graph” have been accepted by IEEE International Conference on Data Engineering (ICDE ’24), Utrecht, Netherlands, May 2024.