Naoise Holohan

According to our database, Naoise Holohan authored at least 14 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection.

Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou, Keith Houck, Ambrish Rawat, Mark Purcell, Naoise Holohan, Mikio Takeuchi, Ryo Kawahara, Nir Drucker, Hayim Shaul, Eyal Kushnir, Omri Soceanu

CoRR, 2023

Random Number Generators and Seeding for Differential Privacy.

Naoise Holohan

CoRR, 2023

2021

Secure Random Sampling in Differential Privacy.

Naoise Holohan, Stefano Braghin

Proceedings of the Computer Security - ESORICS 2021, 2021

Secure k-Anonymization over Encrypted Databases.

Manish Kesarwani, Akshar Kaul, Stefano Braghin, Naoise Holohan, Spiros Antonatos

Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020

The Bounded Laplace Mechanism in Differential Privacy.

Naoise Holohan, Spiros Antonatos, Stefano Braghin, Pól Mac Aonghusa

J. Priv. Confidentiality, 2020

IBM Federated Learning: an Enterprise Framework White Paper V0.1.

Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay

CoRR, 2020

2019

Diffprivlib: The IBM Differential Privacy Library.

Naoise Holohan, Stefano Braghin, Pól Mac Aonghusa, Killian Levacher

CoRR, 2019

AnonTokens: tracing re-identification attacks through decoy records.

Spiros Antonatos, Stefano Braghin, Naoise Holohan, Pol Mac Aonghusa

CoRR, 2019

2018

PRIMA: An End-to-End Framework for Privacy at Scale.

Spiros Antonatos, Stefano Braghin, Naoise Holohan, Yiannis Gkoufas, Pol Mac Aonghusa

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017

Mathematical foundations of differential privacy

Naoise Holohan

PhD thesis, 2017

Optimal Differentially Private Mechanisms for Randomised Response.

Naoise Holohan, Douglas J. Leith, Oliver Mason

IEEE Trans. Inf. Forensics Secur., 2017

(k, ε)-Anonymity: k-Anonymity with ε-Differential Privacy.

Naoise Holohan, Spiros Antonatos, Stefano Braghin, Pol Mac Aonghusa

CoRR, 2017

2016

Differentially private response mechanisms on categorical data.

Naoise Holohan, Douglas J. Leith, Oliver Mason

Discret. Appl. Math., 2016

2015

Differential privacy in metric spaces: Numerical, categorical and functional data under the one roof.

Naoise Holohan, Douglas J. Leith, Oliver Mason

Inf. Sci., 2015