Gonzalo Munilla Garrido

Orcid: 0000-0002-0135-9432

According to our database1, Gonzalo Munilla Garrido authored at least 17 papers between 2020 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
SoK: Data Privacy in Virtual Reality.
Proc. Priv. Enhancing Technol., January, 2024

Improving the Applicability of Differential Privacy in Data Sharing and Analytics Applications.
PhD thesis, 2024

SoK: Privacy-Preserving Data Synthesis.
Proceedings of the IEEE Symposium on Security and Privacy, 2024

2023
Exploring the Privacy Risks of Adversarial VR Game Design.
Proc. Priv. Enhancing Technol., October, 2023

Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry.
Proc. Priv. Enhancing Technol., April, 2023

SoK: The Gap Between Data Rights Ideals and Reality.
CoRR, 2023

Going Incognito in the Metaverse: Achieving Theoretically Optimal Privacy-Usability Tradeoffs in VR.
Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, 2023

2022
Revealing the landscape of privacy-enhancing technologies in the context of data markets for the IoT: A systematic literature review.
J. Netw. Comput. Appl., 2022

Going Incognito in the Metaverse.
CoRR, 2022

Exploring the Unprecedented Privacy Risks of the Metaverse.
CoRR, 2022

Verifying Outsourced Computation in an Edge Computing Marketplace.
CoRR, 2022

Mitigating Sovereign Data Exchange Challenges: A Mapping to Apply Privacy- and Authenticity-Enhancing Technologies.
Proceedings of the Trust, Privacy and Security in Digital Business, 2022

Towards Verifiable Differentially-Private Polling.
Proceedings of the ARES 2022: The 17th International Conference on Availability, Reliability and Security, Vienna,Austria, August 23, 2022

2021
Do I Get the Privacy I Need? Benchmarking Utility in Differential Privacy Libraries.
CoRR, 2021

Exploring privacy-enhancing technologies in the automotive value chain.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Towards a Privacy-Enhancing Tool Based on De- Identification Methods.
Proceedings of the 24th Pacific Asia Conference on Information Systems, 2020

The Use of De-identification Methods for Secure and Privacy-enhancing Big Data Analytics in Cloud Environments.
Proceedings of the 22nd International Conference on Enterprise Information Systems, 2020


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