Diffprivlib: The IBM differential privacy library N Holohan, S Braghin, P Mac Aonghusa, K Levacher
arXiv preprint arXiv:1907.02444, 2019
133 * 2019 IBM Federated Learning: An enterprise framework white paper v0.1 H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ...
arXiv preprint arXiv:2007.10987, 2020
132 2020 Optimal differentially private mechanisms for randomised response N Holohan, DJ Leith, O Mason
IEEE Transactions on Information Forensics and Security 12 (11), 2726-2735, 2017
79 2017 The bounded Laplace mechanism in differential privacy N Holohan, S Antonatos, S Braghin, P Mac Aonghusa
arXiv preprint arXiv:1808.10410, 2018
71 2018 Differential privacy in metric spaces: Numerical, categorical and functional data under the one roof N Holohan, DJ Leith, O Mason
Information Sciences 305, 256-268, 2015
32 2015 ( , )-Anonymity: -Anonymity with -Differential Privacy N Holohan, S Antonatos, S Braghin, P Mac Aonghusa
arXiv preprint arXiv:1710.01615, 2017
25 2017 Extreme points of the local differential privacy polytope N Holohan, DJ Leith, O Mason
Linear Algebra and its Applications 534, 78-96, 2017
18 2017 Secure random sampling in differential privacy N Holohan, S Braghin
Computer Security–ESORICS 2021: 26th European Symposium on Research in …, 2021
15 2021 Prima: an end-to-end framework for privacy at scale S Antonatos, S Braghin, N Holohan, Y Gkoufas, P Mac Aonghusa
2018 IEEE 34th international conference on data engineering (ICDE), 1531-1542, 2018
13 2018 Watermarking anonymized datasets by adding decoys S Antonatos, S Braghin, N Holohan, P MacAonghusa
US Patent 10,997,279, 2021
8 2021 Adaptive anonymization of data using statistical inference A Pascale, N Holohan, P Tommasi, S Deparis
US Patent App. 16/127,694, 2020
8 2020 Sensitive data policy recommendation based on compliance obligations of a data source S Antonatos, S Braghin, N Holohan, K Levacher, R Nair, M Stephenson
US Patent 11,562,087, 2023
6 2023 Applying a differential privacy operation on a cluster of data S Antonatos, S Braghin, N Holohan, P Mac Aonghusa
US Patent 10,769,306, 2020
6 2020 (k, ϵ)-anonymity: k-anonymity with ϵ-differential privacy N Holohan, S Antonatos, S Braghin, P Aonghusa
Data Privacy@ IBMRisk and Privacy, 2017
6 2017 Detecting unauthorized use of sensitive information in content communicated over a network S Antonatos, S Braghin, N Holohan, P Mac Aonghusa
US Patent App. 15/882,583, 2019
5 2019 Federated Continual Learning with Differentially Private Data Sharing G Zizzo, A Rawat, N Holohan, S Tirupathi
Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022
4 2022 Secure -Anonymization over Encrypted Databases M Kesarwani, A Kaul, S Braghin, N Holohan, S Antonatos
arXiv preprint arXiv:2108.04780, 2021
4 2021 Fast linking of anonymized datasets S Antonatos, S Braghin, N Holohan, P MacAonghusa
US Patent 11,132,386, 2021
3 2021 Mathematical Foundations of Differential Privacy N Holohan
Trinity College Dublin, 2017
3 2017 Differentially private response mechanisms on categorical data N Holohan, DJ Leith, O Mason
Discrete Applied Mathematics 211, 86-98, 2016
3 2016