News

  • Feb. 2024: Our paper “LDPTube: Theoretical Utility Benchmark and Enhancement for LDP Mechanisms in High-dimensional Space” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Feb. 2024: Our paper “A Federated Learning Framework Based on Differentially Private Continuous Data Release” is accepted by IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Jan. 2024: Our paper “LDPGuard: Defenses against Data Poisoning Attacks to Local Differential Privacy Protocols” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Jan. 2024: A research project entitled “Federated Graph Management and Querying: Subgraphs, Keywords, and Privacy” is awarded by Research Grant Council with HK$ 4,854,870 (2024.01-2026.12).
  • Dec. 2023: A research project entitled “Towards Provable On-Device Data Privacy for Complex Analytics and Its Applications” is awarded by Huawei Technologies with HK$ 4,854,870 (2024.01-2026.12).
  • Dec. 2023: Our paper “EPS2: Privacy Preserving Set-Valued Data Analysis in the Shuffle Model” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Dec. 2023: Our paper “FRESH: Towards Efficient Graph Queries in an Outsourced Graph” is accepted by IEEE International Conference on Data Engineering (ICDE 2024).
  • Dec. 2023: Our paper “LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy” is accepted by IEEE International Conference on Data Engineering (ICDE 2024).
  • Nov. 2023: Our paper “DPSUR: Accelerating Differentially Private Stochastic Gradient Descent Using Selective Update and Release” is accepted by International Conference on Very Large Databases (VLDB 2024).
  • Nov. 2023: Our paper “Utility-Aware Time Series Data Release with Anomalies under TLDP” is accepted by IEEE Transactions on Mobile Computing (TMC).
  • Oct. 2023: Our paper “DeepMark: A Scalable and Robust Framework for DeepFake Video Detection” is accepted by ACM Transactions on Privacy and Security (TOPS).
  • Sep. 2023: Our paper “Collecting Multi-type and Correlation-Constrained Streaming Sensor Data with Local Differential Privacy” is accepted by ACM Transactions on Sensor Networks (TOSN).
  • Aug. 2023: Our paper “TED+: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Aug. 2023: A research project entitled “本地化差分隐私攻防之数据重构攻击研究” is awarded by NSFC (面上项目) with CNY 500,000 (2024.01-2027.12).
  • Jun. 2023: A General Research Fund (GRF) entitled “Small Leaks Sink Great Ships: Data Recovery Attacks and Defense in Local Differential Privacy” is awarded by Research Grant Council with HK$ 1,096,927 (2024.01-2026.12).
  • Jun. 2023: Our paper “PUTS: Privacy-Preserving and Utility-Enhancing Framework for Trajectory Synthesization” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Jun. 2023: Our paper “Collaborative Sampling for Partial Multi-dimensional Value Collection under Local Differential Privacy” is accepted by IEEE Transactions on Information Forensics and Security (TIFS).
  • May 2023: Our paper “Trajectory Data Collection with Local Differential Privacy” is accepted by International Conference on Very Large Databases (VLDB 2023).
  • Apr. 2023: Our paper “3DFed: Adaptive and Extensible Framework for Covert Backdoor Attack in Federated Learning” is accepted by IEEE Symposium on Security and Privacy (S&P 2023).
  • Feb. 2023: Our paper “Differential Aggregation against General Colluding Attackers” is accepted by IEEE International Conference on Data Engineering (ICDE 2023).
  • Jan. 2023: Our paper “Synthesizing Realistic Trajectory Data with Differential Privacy” is accepted by IEEE Transactions on Intelligent Transportation Systems (TITS).
  • Dec. 2022: Our paper “Stateful Switch: Optimized Time Series Release with Local Differential Privacy” is accepted by IEEE International Conference on Computer Communications (INFOCOM 2023).
  • Sep. 2022: Our paper “TED: Towards Discovering Top-k Edge-Diversified Patterns in a Graph Database” is accepted by ACM International Conference of Management of Data (SIGMOD 2023).
  • Sep. 2022: Our paper “MExMI: Pool-based Active Model Extraction Crossover Membership Inference” is accepted by Conference on Neural Information Processing Systems (NuerIPS 2022).
  • May 2022: Our paper “VINCENT: Towards Efficient Exploratory Subgraph Search in Graph Databases” is accepted by International Conference on Very Large Databases (VLDB 2022).
  • May 2022: Our paper “DDRM: A Continual Frequency Estimation Mechanism with Local Differential Privacy” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Mar. 2022: Our paper “Efficient Verifiably Encrypted ECDSA-Like Signatures and Their Applications” is accepted by IEEE Transactions on Information Forensics and Security (TIFS).
  • Nov. 2021: Our paper “Utility Analysis and Enhancement of LDP Mechanisms in High-Dimensional Space” is accepted by IEEE International Conference on Data Engineering (ICDE 2022).
  • Aug. 2021: A research project entitled “恶意敌手模型下的本地化差分隐私技术探索” is awarded by NSFC (青年科学基金项目) with CNY 300,000 (2022.01-2024.12).
  • Aug. 2021: Our paper “PrivKVM*: Revisiting Key-Value Statistics Estimation with Local Differential Privacy” is accepted by IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Jun. 2021: A research project entitled “Byzantine-Robust Data Collection under Local Differential Privacy Model” is awarded by Research Grant Council, HKSAR with HK$ 838,393 (2022.01-2024.12).
  • Apr. 2021: Our paper “Collecting High-Dimensional and Correlation-Constrained Data with Local Differential Privacy” is accepted by International Conference on Sensing, Communication and Networking (SECON 2021).
  • Dec. 2020: Our paper “Beyond Value Perturbation: Local Differential Privacy in the Temporal Setting” is accepted by IEEE International Conference on Computer Communications (INFOCOM 2021).
  • Dec 2020: Our paper “LF-GDPR: A Framework for Estimating Graph Metrics with Local Differential Privacy” is accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Dec. 2020: Our paper “Protecting Decision Boundary of Machine Learning Model with Differentially Private Perturbation” is accepted by IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Feb. 2020: Our paper “Towards Locally Differentially Private Generic Graph Metric Estimation” is accepted by IEEE International Conference on Data Engineering (ICDE 2020).
  • Aug. 2018: Our paper “PrivKV: Key-Value Data Collection with Local Differential Privacy” is accepted by IEEE Symposium on Security and Privacy (S&P 2019).

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