Zhigang Lu

Orcid: 0000-0001-5102-6217

Affiliations:
  • Western Sydney University, School of Computer, Data and Mathematical Sciences, Sydney, NSW, Australia
  • James Cook University, College of Science and Engineering, Townsville, QLD, Australia
  • Macquarie University, School of Computing, Sydney, NSW, Australia (2020 - 2023)
  • University of Adelaide, School of Computer Science, SA, Australia (PhD 2019)


According to our database1, Zhigang Lu authored at least 24 papers between 2015 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2025
PriDM: Effective and Universal Private Data Recovery via Diffusion Models.
IEEE Trans. Dependable Secur. Comput., 2025

Practical, Private Assurance of the Value of Collaboration via Fully Homomorphic Encryption.
Proc. Priv. Enhancing Technol., 2025

GAP-Diff: Protecting JPEG-Compressed Images from Diffusion-based Facial Customization.
Proceedings of the 32nd Annual Network and Distributed System Security Symposium, 2025

2024
${\sf VeriDIP}$VeriDIP: Verifying Ownership of Deep Neural Networks Through Privacy Leakage Fingerprints.
IEEE Trans. Dependable Secur. Comput., 2024

Reconstruction of Differentially Private Text Sanitization via Large Language Models.
CoRR, 2024

dp-promise: Differentially Private Diffusion Probabilistic Models for Image Synthesis.
Proceedings of the 33rd USENIX Security Symposium, 2024

Efficient Constrained K-center Clustering with Background Knowledge.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
VeriDIP: Verifying Ownership of Deep Neural Networks through Privacy Leakage Fingerprints.
CoRR, 2023

Practical, Private Assurance of the Value of Collaboration.
CoRR, 2023

2022
Augmentation-Based Edge Differentially Private Path Publishing in Networks.
IEEE Trans. Netw. Serv. Manag., December, 2022

A Differentially Private Framework for Deep Learning With Convexified Loss Functions.
IEEE Trans. Inf. Forensics Secur., 2022

2021
Differentially Private $k$k-Means Clustering With Convergence Guarantee.
IEEE Trans. Dependable Secur. Comput., 2021

Trace Recovery: Inferring Fine-grained Trace of Energy Data from Aggregates.
Proceedings of the 18th International Conference on Security and Cryptography, 2021

Trace Recovery: Attacking and Defending the User Privacy in Smart Meter Data Analytics.
Proceedings of the E-Business and Telecommunications - 18th International Conference, 2021

TableGAN-MCA: Evaluating Membership Collisions of GAN-Synthesized Tabular Data Releasing.
Proceedings of the CCS '21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15, 2021

2020
Differentially Private k-Means Clustering with Guaranteed Convergence.
CoRR, 2020

Protect Edge Privacy in Path Publishing with Differential Privacy.
CoRR, 2020

2019
A Temporal Caching-Aware Dummy Selection Location Algorithm.
Proceedings of the 20th International Conference on Parallel and Distributed Computing, 2019

A Convergent Differentially Private k-Means Clustering Algorithm.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2017
A New Lower Bound of Privacy Budget for Distributed Differential Privacy.
Proceedings of the 18th International Conference on Parallel and Distributed Computing, 2017

Secured Privacy Preserving Data Aggregation with Semi-honest Servers.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

2015
A Faster Algorithm to Build New Users Similarity List in Neighbourhood-based Collaborative Filtering.
CoRR, 2015

An accuracy-assured privacy-preserving recommender system for internet commerce.
Comput. Sci. Inf. Syst., 2015

A Security-assured Accuracy-maximised Privacy Preserving Collaborative Filtering Recommendation Algorithm.
Proceedings of the 19th International Database Engineering & Applications Symposium, 2015


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