Differential privacy in metric spaces: Numerical, categorical and functional data under the one roof. - Naoise Holohan; Douglas J. Leith; Oliver Mason (Inf. Sci., 2015)

Differentially private response mechanisms on categorical data. - Naoise Holohan; Douglas J. Leith; Oliver Mason (Discret. Appl. Math., 2016)

(k, ε)-Anonymity: k-Anonymity with ε-Differential Privacy. - Naoise Holohan; Spiros Antonatos; Stefano Braghin; Pol Mac Aonghusa (CoRR, 2017)

Optimal Differentially Private Mechanisms for Randomised Response. - Naoise Holohan; Douglas J. Leith; Oliver Mason (IEEE Trans. Inf. Forensics Secur., 2017)

Mathematical foundations of differential privacy - Naoise Holohan (2017)

PRIMA: An End-to-End Framework for Privacy at Scale. - Spiros Antonatos; Stefano Braghin; Naoise Holohan; Yiannis Gkoufas; Pol Mac Aonghusa (ICDE, 2018)

AnonTokens: tracing re-identification attacks through decoy records. - Spiros Antonatos; Stefano Braghin; Naoise Holohan; Pol Mac Aonghusa (CoRR, 2019)

Diffprivlib: The IBM Differential Privacy Library. - Naoise Holohan; Stefano Braghin; Pól Mac Aonghusa; Killian Levacher (CoRR, 2019)

IBM Federated Learning: an Enterprise Framework White Paper V0.1. - Heiko Ludwig; Nathalie Baracaldo; Gegi Thomas; Yi Zhou 015; Ali Anwar 001; Shashank Rajamoni; Yuya Jeremy Ong; Jayaram Radhakrishnan; Ashish Verma 001; Mathieu Sinn; Mark Purcell; Ambrish Rawat; et al. (CoRR, 2020)

The Bounded Laplace Mechanism in Differential Privacy. - Naoise Holohan; Spiros Antonatos; Stefano Braghin; Pól Mac Aonghusa (J. Priv. Confidentiality, 2020)

Secure k-Anonymization over Encrypted Databases. - Manish Kesarwani; Akshar Kaul; Stefano Braghin; Naoise Holohan; Spiros Antonatos (CLOUD, 2021)

Secure Random Sampling in Differential Privacy. - Naoise Holohan; Stefano Braghin (ESORICS (2), 2021)

Random Number Generators and Seeding for Differential Privacy. - Naoise Holohan (CoRR, 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 015; Keith Houck; Ambrish Rawat; Mark Purcell; Naoise Holohan; Mikio Takeuchi; Ryo Kawahara; Nir Drucker; et al. (CoRR, 2023)

Securing Floating-Point Arithmetic for Noise Addition. - Naoise Holohan; Stefano Braghin; Mohamed Suliman 002 (CCS, 2024)