Highlights
- Publications at big four security conferences (20 papers): Oakland (’25), Security (’24, ’23c, ’23b, ’23a, ’22b, ’22a, ’21), CCS (’24b, ’24a, ’23, ’22c, ’22b, ’22a, ’21c, ’21b, ’21a, ’18), NDSS (’24a, ’24b).
- Publications at top-tier database conferences (2 papers): VLDB (’23), ICDE (’24).
- Publications at top-tier machine learning conferences (2 papers): ICML (’24, ’23).
- Other top-tier computer science conferences/journals (3 papers): KDD (’23), TDSC (’18), TIFS (’18).
- Corresponding author “#” (9 papers); co-first author “+” (1 paper).
2025
[Oakland’25, CCF-A] SoK: Dataset Copyright Auditing in Machine Learning Systems
Linkang Du, Xuanru Zhou, Min Chen, Chusong Zhang, Zhou Su, Peng Cheng, Jiming Chen, Zhikun Zhang#
To appear in IEEE S&P 2025
2024
[CCS’24b, CCF-A] S2NeRF: Privacy-preserving Training Framework for NeRF
Bokang Zhang, Yanglin Zhang, Zhikun Zhang#, Jinglan Yang, Lingying Huang, Junfeng Wu
In Proceedings of ACM CCS 2024
[CCS’24a, CCF-A] The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy Risks
Xiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan, Lei Jin, Zihao Wang, Liya Su, Zhikun Zhang, Xiaofeng Wang, Haixu Tang
In Proceedings of ACM CCS 2024
[Security’24, CCF-A] DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
Zihao Wang, Rui Zhu, Dongruo Zhou, Zhikun Zhang, John Mitchell, Haixu Tang, Xiaofeng Wang
In Proceedings of USENIX Security 2024
[NDSS’24b, CCF-A, Distinguished Paper Award] LMSanitator: Defending Task-agnostic Backdoors Against Prompt-tuning
Chengkun Wei, Wenlong Meng, Zhikun Zhang#, Min Chen, Minghu Zhao, Wenjing Fang, Lei Wang, Zihui Zhang, Wenzhi Chen
In Proceedings of NDSS 2024
[NDSS’24a, CCF-A] ORL-Auditor: Dataset Auditing in Offline Deep Reinforcement Learning
Linkang Du, Min Chen, Mingyang Sun, Shouling Ji, Peng Cheng, Jiming Chen, Zhikun Zhang#
In Proceedings of NDSS 2024
[ICDE’24, CCF-A] Real-Time Trajectory Synthesis with Local Differential Privacy
Yujia Hu, Yuntao Du, Zhikun Zhang, Ziquan Fang, Lu Chen, Kai Zheng, Yunjun Gao
In Proceedings of ICDE 2024
[ICML’24, CCF-A] TrustLLM: Trustworthiness in Large Language Models
Lichao Sun, et al. Zhikun Zhang, et al.
In Proceedings of ICML 2024
[AsiaCCS’24b, CCF-C] PARL: Poisoning Attacks Against Reinforcement Learning-based Recommender Systems
Linkang Du, Quan Yuan, Min Chen, Mingyang Sun, Peng Cheng, Jiming Chen, Zhikun Zhang#
In Proceedings of AsiaCCS 2024
[AsiaCCS’24a, CCF-C] FakePCD: Fake Point Cloud Detection via Source Attribution
Yiting Qu, Zhikun Zhang, Yun Shen, Michael Backes, Yang Zhang
In Proceedings of AsiaCCS 2024
[TII’24, CCF-C] Stealthy Black-Box Attack With Dynamic Threshold Against MARL-Based Traffic Signal Control System
Yan Ren, Heng Zhang, Linkang Du, Zhikun Zhang, Jian Zhang, Hongran Li
In IEEE Transactions on Industrial Informatics (TII), 2024
[PPAI’24] De-amplifying Bias from Differential Privacy in Language Model Fine-tuning [Spotlight]
Sanjari Srivastava, Piotr Mardziel, Zhikhun Zhang, Archana Ahlawat, Anupam Datta, John C Mitchell
In AAAI-PPAI 2024
[软件学报’24] 基于自适应剪枝的满足本地差分隐私的真值发现算法
张朋飞, 朱伊波, 程祥, 张治坤, 刘西蒙, 孙笠, 方贤进, 张吉
软件学报，2024
2023
[CCS’23, CCF-A] DPMLBench: Holistic Evaluation of Differentially Private Machine Learning
Chengkun Wei, Minghu Zhao, Zhikun Zhang#, Min Chen, Wenlong Meng, Bo Liu, Yuan Fan, Wenzhi Chen
In Proceedings of ACM CCS 2023
[Security’23c, CCF-A] FACE-AUDITOR: Data Auditing in Facial Recognition Systems
Min Chen, Zhikun Zhang#, Tianhao Wang, Michael Backes, Yang Zhang
In Proceedings of USENIX Security 2023
[Security’23b, CCF-A] PrivGraph: Differentially Private Graph Data Publication by Exploiting Community Information
Quan Yuan, Zhikun Zhang, Linkang Du, Min Chen, Peng Cheng, Mingyang Sun
In Proceedings of USENIX Security 2023
[Security’23a, CCF-A] PrivTrace: Differentially Private Trajectory Synthesis by Adaptive Markov Model
Haiming Wang, Zhikun Zhang#, Tianhao Wang, Shibo He, Michael Backes, Jiming Chen, Yang Zhang
In Proceedings of USENIX Security 2023
[VLDB’23, CCF-A] LDPTrace: Locally Differentially Private Trajectory Synthesis
Yuntao Du, Yujia Hu, Zhikun Zhang, Ziquan Fang, Lu Chen, Baihua Zheng, Yunjun Gao
In Proceedings of VLDB 2023
[KDD’23, CCF-A] CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution
Yuxiang Guo, Lu Chen, Zhengjie Zhou, Baihua Zheng, Ziquan Fang, Zhikun Zhang, Yuren Mao, Yunjun Gao
In Proceedings of KDD 2023
[ICML’23, CCF-A] Generated Graph Detection
Yihan Ma, Zhikun Zhang, Ning Yu, Xinlei He, Michael Backes, Yun Shen, Yang Zhang
In Proceedings of ICML 2023
[ACSAC’23, CCF-B] Differentially Private Resource Allocation
Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li
In Proceedings of ACSAC 2023
[ICC’23, CCF-C] Making Watermark Survive Model Extraction Attacks in Graph Neural Networks
Haiming Wang, Zhikun Zhang, Min Chen, Shibo He
In Proceedings of IEEE ICC 2023
2022
[Security’22b, CCF-A] Inference Attacks Against Graph Neural Networks
Zhikun Zhang, Min Chen, Michael Backes, Yun Shen, Yang Zhang
In Proceedings of USENIX Security 2022
[Security’22a, CCF-A] ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models
Yugeng Liu, Rui Wen, Xinlei He, Ahmed Salem, Zhikun Zhang, Michael Backes, Emiliano De Cristofaro, Mario Fritz, Yang Zhang
In Proceedings of USENIX Security 2022
[CCS’22c, CCF-A] On the Privacy Risks of Cell-Based NAS Architectures
Hai Huang, Zhikun Zhang, Yun Shen, Michael Backes, Qi Li, Yang Zhang
In Proceedings of ACM CCS 2022
[CCS’22b, CCF-A] Graph Unlearning
Min Chen, Zhikun Zhang#, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
In Proceedings of ACM CCS 2022
[CCS’22a, CCF-A] Finding MNEMON: Reviving Memories of Node Embeddings
Yun Shen, Yufei Han, Zhikun Zhang, Min Chen, Ting Yu, Michael Backes, Yang Zhang, Gianluca Stringhini
In Proceedings of ACM CCS 2022
[PPNA’22, CCF-C] Backdoor Attacks Against Deep Reinforcement Learning Based Traffic Signal Control Systems
Heng Zhang, Jun Gu, Zhikun Zhang, Linkang Du, Yongmin Zhang, Yan Ren, Jian Zhang, Hongran Li
In Peer-to-Peer Networking and Applications (PPNA), 2022
[FSN’22] Neural Network in Food Analytics
Peihua Ma, Zhikun Zhang, Xiaoxue Jia, Xiaoke Peng, Zhi Zhang, Kevin Tarwa, Cheng-I Wei, Fuguo Liu, Qin Wang
In Food Science and Nutrition, 2022
[FoodChem’22] Deep Learning Accurately Predicts Food Categories and Nutrients Based on Ingredient Statements
Peihua Ma, Zhikun Zhang, Ying Li, Ning Yu, Jiping Sheng, Hande Küçük McGinty, Qin Wang, Jaspreet KC Ahuja
In Food Chemistry, 2022
2021
[Security’21, CCF-A] PrivSyn: Differentially Private Data Synthesis
Zhikun Zhang, Tianhao Wang, Ninghui Li, Jean Honorio, Michael Backes, Shibo He, Jiming Chen, Yang Zhang
In Proceedings of USENIX Security 2021
[CCS’21c, CCF-A] When Machine Unlearning Jeopardize Privacy
Min Chen, Zhikun Zhang+, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang
In Proceedings of ACM CCS 2021
[CCS’21b, CCF-A] Continuous Release of Data Streams under both Centralized and Local Differential Privacy
Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su, Yueqiang Cheng, Zhou Li, Ninghui Li, Somesh Jha
In Proceedings of ACM CCS 2021
[CCS’21a, CCF-A] AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy
Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, Jiming Chen
In Proceedings of ACM CCS 2021
[JPC’21] DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges
Ninghui Li, Zhikun Zhang, Tianhao Wang
In Journal of Privacy and Confidentiality (JPC), 2021
Before 2020
[Ph.D. Thesis] Data Utility Optimization for Local Differential Privacy
Zhikun Zhang
Ph.D. Thesis (In Chinese, Nomination Award for Outstanding Doctoral Thesis of Zhejiang University and Zhejiang Province)
[CCS’18, CCF-A] CALM: Consistent Adaptive Local Marginal for Marginal Release under Local Differential Privacy
Zhikun Zhang, Tianhao Wang, Ninghui Li, Shibo He, Jiming Chen
In Proceedings of ACM CCS 2018
[TIFS’18, CCF-A] REAP: An Efficient Incentive Mechanism for Reconciling Aggregation Accuracy and Individual Privacy in Crowdsensing
Zhikun Zhang, Shibo He, Junshan Zhang, Jiming Chen
In IEEE Transactions on Information Forensics & Security (TIFS), 2018
[TDSC’18, CCF-A] Bilateral Privacy-preserving Utility Maximization Protocol in Database-driven Cognitive Radio Networks
Zhikun Zhang, Heng Zhang, Shibo He, Peng Cheng
In IEEE Transactions on Dependable and Secure Computing (TDSC), 2018
[IoTJ’18, CCF-C] Throughput Modeling and Analysis of Random Access in Narrow-band Internet of Things
Yuyi Sun, Fei Tong, Zhikun Zhang, Shibo He
In IEEE Internet of Things Journal, 2018
[GLOBECOM’17, CCF-C] Re-DPoctor: Real-time Health Data Releasing with w-day Differential Privacy
Jiajun Zhang, Xiaohui Liang, Shibo He, Zhikun Zhang, Zhiguo Shi
In proceedings of IEEE GLOBECOM 2017
[MASS’15, CCF-C] Achieving Bilateral Utility Maximization and Location Privacy Preservation in Database-driven Cognitive Radio Networks
Zhikun Zhang, Heng Zhang, Shibo He, Peng Cheng
In proceedings of IEEE MASS 2015
Technical Report
[arXiv’20] Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning
Yang Zou, Zhikun Zhang, Michael Backes, Yang Zhang
Technical Report
[arXiv’17] LEPA: Incentivizing Long-term Privacy-perserving Data Aggregation in Crowdsensing
Zhikun Zhang, Shibo He, Mengyuan Zhang, Jiming Chen
Technical report