Dr Erik Buchholz

Dr Erik Buchholz

Research Associate

Education:

  • PhD – UNSW Sydney, Australia.
    • Thesis Title: The Long Road to Trajectory Privacy: Differential Privacy and Generative Models.
  • Master of Science with Distinction – RWTH Aachen, Germany.
    • Master's Thesis: Privacy-Preserving Exchange of Process Parameters.
  • Bachelor of Science with Distinction – RWTH Aachen, Germany.
    • Bachelor's Thesis: A User-controlled Data Market for Privacy-preserving Data Analyses.

 

Qualifications:

Engineering
Computer Science and Engineering

Dr. Erik Buchholz is a Postdoctoral Researcher in Cybersecurity at UNSW Sydney and GuardWare Australia, where his work focuses on encrypting unstructured data in the defence supply chain. His broader research interests include privacy-enhancing technologies, differential privacy, generative models, and applied cryptography.

He completed his PhD at UNSW Sydney and CSIRO’s Data61, supported by the competitive CSCRC scholarship. His doctoral research investigated the privacy of location trajectories using differential privacy and generative models. This research was recognised with the Best Paper Award at PST 2024 and publications at top venues such as PETS, ACSAC, and AsiaCCS. Erik's thesis identified shortcomings of existing privacy mechanisms, proposed a novel reconstruction attack, and explored synthetic data generation as a privacy-preserving solution.

In 2025, he was named one of Australia’s Top100 Future Leaders. He is deeply committed to open science, releasing the code for all his publications on GitHub. He has supervised over 20 students on theses, capstone projects, and internships, with multiple projects leading to international publications. Moreover, he contributed to the AGSE Industry PhD program as an advisory board member and acted as system administrator his research group.

He frequently presents his work to both academic and public audiences, with recognition including the AGSE 3MT People’s Choice Award and the SecEdu Best Poster Award. These experiences highlight his commitment to making research accessible beyond academia. He welcomes opportunities to collaborate and give talks.

Location
School of Computer Science and Engineering (CSE), Level 4, Building K17, UNSW SYDNEY 2052.
  • Journal articles | 2024
    Buchholz E; Abuadbba A; Wang S; Nepal S; Kanhere SS, 2024, 'SoK: Can Trajectory Generation Combine Privacy and Utility?', Proceedings on Privacy Enhancing Technologies, 2024, pp. 75 - 93, http://dx.doi.org/10.56553/popets-2024-0068
  • Preprints | 2025
    Buchholz E; Fernandes N; Nguyen DD; Abuadbba A; Nepal S; Kanhere SS, 2025, What is the Cost of Differential Privacy for Deep Learning-Based Trajectory Generation?, http://dx.doi.org/10.48550/arxiv.2506.09312
    Preprints | 2024
    Buchholz E; Abuadbba A; Wang S; Nepal S; Kanhere SS, 2024, SoK: Can Trajectory Generation Combine Privacy and Utility?, http://dx.doi.org/10.48550/arxiv.2403.07218
    Conference Papers | 2024
    D'Silva N; Shahi T; Dokk Husveg OT; Sanjeeve A; Buchholz E; Kanhere SS, 2024, 'Demystifying Trajectory Recovery from Ash: An Open-Source Evaluation and Enhancement', in 2024 17th International Conference on Security of Information and Networks Sin 2024, http://dx.doi.org/10.1109/SIN63213.2024.10871881
    Preprints | 2024
    D'Silva N; Shahi T; Husveg ØTD; Sanjeeve A; Buchholz E; Kanhere SS, 2024, Demystifying Trajectory Recovery From Ash: An Open-Source Evaluation and Enhancement, http://dx.doi.org/10.48550/arxiv.2409.14645
    Conference Papers | 2024
    Merhi J; Buchholz E; Kanhere SS, 2024, 'Synthetic Trajectory Generation Through Convolutional Neural Networks', in 2024 21st Annual International Conference on Privacy Security and Trust Pst 2024, http://dx.doi.org/10.1109/PST62714.2024.10788061
    Preprints | 2024
    Merhi J; Buchholz E; Kanhere SS, 2024, Synthetic Trajectory Generation Through Convolutional Neural Networks, http://dx.doi.org/10.48550/arxiv.2407.16938
    Conference Papers | 2022
    Buchholz E; Abuadbba A; Wang S; Nepal S; Kanhere SS, 2022, 'Reconstruction Attack on Differential Private Trajectory Protection Mechanisms', in ACM International Conference Proceeding Series, pp. 279 - 292, http://dx.doi.org/10.1145/3564625.3564628
    Preprints | 2022
    Buchholz E; Abuadbba A; Wang S; Nepal S; Kanhere SS, 2022, Reconstruction Attack on Differential Private Trajectory Protection Mechanisms, http://dx.doi.org/10.1145/3564625.3564628
    Preprints | 2021
    Pennekamp J; Buchholz E; Dahlmanns M; Kunze I; Braun S; Wagner E; Brockmann M; Wehrle K; Henze M, 2021, Collaboration is not Evil: A Systematic Look at Security Research for Industrial Use, http://dx.doi.org/10.48550/arxiv.2112.11417
    Conference Papers | 2020
    Matzutt R; Pennekamp J; Buchholz E; Wehrle K, 2020, 'Utilizing Public Blockchains for the Sybil-Resistant Bootstrapping of Distributed Anonymity Services', in Proceedings of the 15th ACM Asia Conference on Computer and Communications Security Asia Ccs 2020, pp. 531 - 542, http://dx.doi.org/10.1145/3320269.3384729
    Preprints | 2020
    Matzutt R; Pennekamp J; Buchholz E; Wehrle K, 2020, Utilizing Public Blockchains for the Sybil-Resistant Bootstrapping of Distributed Anonymity Services, http://dx.doi.org/10.48550/arxiv.2004.06386
    Conference Papers | 2020
    Pennekamp J; Buchholz E; Dahlmanns M; Kunze I; Braun S; Wagner E; Brockmann M; Wehrle K; Henze M, 2020, 'Collaboration is not Evil: A Systematic Look at Security Research for Industrial Use', in Proceedings 2020 Learning from Authoritative Security Experiment Results Workshop, Applied Computer Security Associates, presented at Learning from Authoritative Security Experiment Results, http://dx.doi.org/10.14722/laser-acsac.2020.23088
    Conference Papers | 2020
    Pennekamp J; Buchholz E; Lockner Y; Dahlmanns M; Xi T; Fey M; Brecher C; Hopmann C; Wehrle K, 2020, 'Privacy-Preserving Production Process Parameter Exchange', in ACM International Conference Proceeding Series, pp. 510 - 525, http://dx.doi.org/10.1145/3427228.3427248

My Teaching

  • 2022-2025 | Tutor | UNSW Sydney
    • Subject: COMP3331/93331 – Computer Networks and Applications
    • Preparation of teaching materials
    • In-Person Teaching of labs & tutorials
    • Marking of assignments
    • MyExperience: Higher student satisfaction than Uni, Faculty, and School average.
  • 2018 | Tutor | RWTH Aachen
    • Subject: Operating Systems and System Software
  • 2017 | Tutor | UTS Housing
    • Subject: “Introduction to Programming in Python”
    • Independent teaching
    • Establishment of a new course for students of all faculties including creation of materials, preparation, and presentation
  • 2016/17 | Tutor | RWTH Aachen
    • Subject: Introduction to Management Science (IT for business students)
  • 2016 | Tutor | RWTH Aachen
    • Subject: Operating Systems and System Software
  • 2015/16 | Tutor | RWTH Aachen
    • Subject: Computability and Complexity
  • 2015 | Tutor | RWTH Aachen
    • Subject: Operating Systems and System Software