Understanding and assessment of privacy risks in machine learning systems.
PhD thesis, 2024
PSGraph: Differentially Private Streaming Graph Synthesis by Considering Temporal Dynamics.
CoRR, 2024
SoK: Dataset Copyright Auditing in Machine Learning Systems.
CoRR, 2024
LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024
ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning.
Proceedings of the 31st Annual Network and Distributed System Security Symposium, 2024
PARL: Poisoning Attacks Against Reinforcement Learning-based Recommender Systems.
Proceedings of the 19th ACM Asia Conference on Computer and Communications Security, 2024
PrivGraph: Differentially Private Graph Data Publication by Exploiting Community Information.
Proceedings of the 32nd USENIX Security Symposium, 2023
FACE-AUDITOR: Data Auditing in Facial Recognition Systems.
Proceedings of the 32nd USENIX Security Symposium, 2023
Making Watermark Survive Model Extraction Attacks in Graph Neural Networks.
Proceedings of the IEEE International Conference on Communications, 2023
DPMLBench: Holistic Evaluation of Differentially Private Machine Learning.
Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, 2023
Inference Attacks Against Graph Neural Networks.
Proceedings of the 31st USENIX Security Symposium, 2022
Finding MNEMON: Reviving Memories of Node Embeddings.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022
When Machine Unlearning Jeopardizes Privacy.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021
RF-Based Charger Placement for Duty Cycle Guarantee in Battery-Free Sensor Networks.
IEEE Commun. Lett., 2015