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Nathalie Baracaldo
Nathalie Baracaldo
IBM Almaden Research Center, Senior Research Staff Member, Ph.D.
Verified email at pitt.edu - Homepage
Title
Cited by
Cited by
Year
A hybrid approach to privacy-preserving federated learning
S Truex, N Baracaldo, A Anwar, T Steinke, H Ludwig, R Zhang, Y Zhou
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
9212019
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
B Chen, W Carvalho, N Baracaldo, H Ludwig, B Edwards, T Lee, I Molloy, ...
arXiv preprint arXiv:1811.03728, 2018
7632018
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
5532018
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning
R Xu, N Baracaldo, Y Zhou, A Anwar, H Ludwig
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
3372019
Tifl: A tier-based federated learning system
Z Chai, A Ali, S Zawad, S Truex, A Anwar, N Baracaldo, Y Zhou, H Ludwig, ...
Proceedings of the 29th International Symposium on High-Performance Parallel …, 2020
2662020
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
1332020
Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach
N Baracaldo, B Chen, H Ludwig, JA Safavi
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security …, 2017
1302017
An Adaptive Risk Management and Access Control Framework to Mitigate Insider Threats
N Baracaldo, J Joshi
Computers & Security 39, 237-254, 2013
1012013
Privacy-preserving process mining: Differential privacy for event logs
F Mannhardt, A Koschmider, N Baracaldo, M Weidlich, J Michael
Business & Information Systems Engineering 61, 595-614, 2019
972019
Towards Taming the Resource and Data Heterogeneity in Federated Learning
Z Chai, H Fayyaz, Z Fayyaz, A Anwar, Y Zhou, N Baracaldo, H Ludwig, ...
2019 {USENIX} Conference on Operational Machine Learning (OpML 19), 19-21, 2019
862019
Detecting Poisoning Attacks on Machine Learning in IoT Environments
RZ Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Amir Safavi
IEEE International Congress on Internet of Things (ICIOT), 2018
852018
Privacy-preserving machine learning: Methods, challenges and directions
R Xu, N Baracaldo, J Joshi
arXiv preprint arXiv:2108.04417, 2021
832021
Mitigating Bias in Federated Learning
A Abay, Y Zhou, N Baracaldo, S Rajamoni, E Chuba, H Ludwig
arXiv preprint arXiv:2012.02447, 2020
812020
A trust-and-risk aware RBAC framework: tackling insider threat
N Baracaldo, J Joshi
Proceedings of the 17th ACM symposium on Access Control Models and …, 2012
712012
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
R Xu, N Baracaldo, Y Zhou, A Anwar, J Joshi, H Ludwig
Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security …, 2021
662021
Federated Unlearning: How to Efficiently Erase a Client in FL?
A Halimi, S Kadhe, A Rawat, N Baracaldo
arXiv preprint arXiv:2207.05521, 2022
512022
Curse or redemption? how data heterogeneity affects the robustness of federated learning
S Zawad, A Ali, PY Chen, A Anwar, Y Zhou, N Baracaldo, Y Tian, F Yan
Proceedings of the AAAI Conference on Artificial Intelligence 35 (12), 10807 …, 2021
512021
User-centered and privacy-driven process mining system design for IoT
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
Information Systems Engineering in Responsible Information Systems: CAiSE …, 2019
482019
User-centered and privacy-driven process mining system design for IoT
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
Information Systems Engineering in Responsible Information Systems: CAiSE …, 2019
482019
User-centered and privacy-driven process mining system design for IoT
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
Information Systems Engineering in Responsible Information Systems: CAiSE …, 2019
482019
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Articles 1–20