One Paper Accepted by SIGKDD 2025
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).
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).
Our paper “Federated Heavy Hitter Analytics with Local Differential Privacy” is accepted by International Conference of Management of Data (SIGMOD 2025)”. Our paper “Membership Inference Attacks and Defenses in Federated Learning: A Survey” is accepted by ACM Computing Surveys.
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).
Our following papers are accepted by IEEE International Conference on Data Engineering (ICDE ’24), Utrecht, Netherlands, May 2024 as full research papers. Congratulations to all authors!
Our paper “DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release” has been accepted by PVLDB 2024.
Our paper “TED+Utility-Aware Time Series Data Release with Anomalies under TLDP” has been accepted by IEEE Transactions on Mobile Computing (TMC). Our paper “A Utility-aware Anonymization Model for Multiple Sensitive Attributes Based on Association Concealment” has been accepted by IEEE Transactions on Dependable and Secure Computing (TDSC). Our paper “DeepMark: A Scalable and Robust Framework…
Our paper “TED+: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database” has been accepted by IEEE TKDE. Our paper “Secure Traffic Monitoring with Spatio-temporal Metadata Protection Using Oblivious RAM” has been accepted by IEEE Transactions on Intelligent Transportation Systems. Our paper “Collecting Multi-type and Correlation-Constrained Streaming Sensor Data with Local Differential Privacy” has been…
Our paper “Collaborative Sampling for Partial Multi-dimensional Value Collection under Local Differential Privacy” has been accepted by IEEE TIFS. Our paper “PUTS: Privacy-Preserving and Utility-Enhancing Framework for Trajectory Synthesization” has been accepted by IEEE TKDE.
Our paper “Trajectory Data Collection with Local Differential Privacy” has been accepted by PVLDB 2023.
Our paper “3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning” has been accepted by IEEE S&P 2023.