A Security-assured Accuracy-maximised Privacy Preserving Collaborative Filtering Recommendation Algorithm. - Zhigang Lu 001; Hong Shen 001 (IDEAS, 2015)

An accuracy-assured privacy-preserving recommender system for internet commerce. - Zhigang Lu 001; Hong Shen 001 (Comput. Sci. Inf. Syst., 2015)

A Faster Algorithm to Build New Users Similarity List in Neighbourhood-based Collaborative Filtering. - Zhigang Lu 001; Hong Shen 001 (CoRR, 2015)

Secured Privacy Preserving Data Aggregation with Semi-honest Servers. - Zhigang Lu 001; Hong Shen 001 (PAKDD (2), 2017)

A New Lower Bound of Privacy Budget for Distributed Differential Privacy. - Zhigang Lu 001; Hong Shen 001 (PDCAT, 2017)

A Convergent Differentially Private k-Means Clustering Algorithm. - Zhigang Lu 001; Hong Shen 001 (PAKDD (1), 2019)

A Temporal Caching-Aware Dummy Selection Location Algorithm. - Xuejiao Mu; Hong Shen 001; Zhigang Lu 001 (PDCAT, 2019)

Protect Edge Privacy in Path Publishing with Differential Privacy. - Zhigang Lu 001; Hong Shen 001 (CoRR, 2020)

Differentially Private k-Means Clustering with Guaranteed Convergence. - Zhigang Lu 001; Hong Shen 001 (CoRR, 2020)

TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing. - Aoting Hu; Renjie Xie; Zhigang Lu 001; Aiqun Hu; Minhui Xue 001 (CCS, 2021)

Trace Recovery: Attacking and Defending the User Privacy in Smart Meter Data Analytics. - Nazim Uddin Sheikh; Zhigang Lu 001; Hassan Jameel Asghar; Mohamed Ali Kâafar (ICETE (Selected Papers), 2021)

Trace Recovery: Inferring Fine-grained Trace of Energy Data from Aggregates. - Nazim Uddin Sheikh; Zhigang Lu 001; Hassan Asghar 001; Mohamed Ali Kâafar (SECRYPT, 2021)

Differentially Private $k$k-Means Clustering With Convergence Guarantee. - Zhigang Lu 001; Hong Shen 001 (IEEE Trans. Dependable Secur. Comput., 2021)

A Differentially Private Framework for Deep Learning With Convexified Loss Functions. - Zhigang Lu 001; Hassan Jameel Asghar; Mohamed Ali Kâafar; Darren Webb; Peter Dickinson (IEEE Trans. Inf. Forensics Secur., 2022)

Augmentation-Based Edge Differentially Private Path Publishing in Networks. - Zhigang Lu 001; Hong Shen 001 (IEEE Trans. Netw. Serv. Manag., 2022)

Practical, Private Assurance of the Value of Collaboration. - Hassan Jameel Asghar; Zhigang Lu 001; Zhongrui Zhao; Dali Kaafar (CoRR, 2023)

VeriDIP: Verifying Ownership of Deep Neural Networks through Privacy Leakage Fingerprints. - Aoting Hu; Zhigang Lu 001; Renjie Xie; Minhui Xue 001 (CoRR, 2023)

Efficient Constrained K-center Clustering with Background Knowledge. - Longkun Guo; Chaoqi Jia; Kewen Liao; Zhigang Lu 001; Minhui Xue 001 (AAAI, 2024)

dp-promise: Differentially Private Diffusion Probabilistic Models for Image Synthesis. - Haichen Wang; Shuchao Pang; Zhigang Lu 001; Yihang Rao; Yongbin Zhou; Minhui Xue 001 (USENIX Security Symposium, 2024)

Reconstruction of Differentially Private Text Sanitization via Large Language Models. - Shuchao Pang; Zhigang Lu 001; Haichen Wang; Peng Fu; Yongbin Zhou; Minhui Xue 001; Bo Li 026 (CoRR, 2024)

${ sf VeriDIP}$VeriDIP: Verifying Ownership of Deep Neural Networks Through Privacy Leakage Fingerprints. - Aoting Hu; Zhigang Lu 001; Renjie Xie; Minhui Xue 001 (IEEE Trans. Dependable Secur. Comput., 2024)

GAP-Diff: Protecting JPEG-Compressed Images from Diffusion-based Facial Customization. - Haotian Zhu; Shuchao Pang; Zhigang Lu 001; Yongbin Zhou; Minhui Xue 001 (NDSS, 2025)

Practical, Private Assurance of the Value of Collaboration via Fully Homomorphic Encryption. - Hassan Jameel Asghar; Zhigang Lu 001; Zhongrui Zhao; Dali Kaafar (Proc. Priv. Enhancing Technol., 2025)

PriDM: Effective and Universal Private Data Recovery via Diffusion Models. - Shuchao Pang; Yihang Rao; Zhigang Lu 001; Haichen Wang; Yongbin Zhou; Minhui Xue 001 (IEEE Trans. Dependable Secur. Comput., 2025)