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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
9652019
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
7992018
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
5862018
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
3512019
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
2772020
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
1422020
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
1402017
An Adaptive Risk Management and Access Control Framework to Mitigate Insider Threats
N Baracaldo, J Joshi
Computers & Security 39, 237-254, 2013
1022013
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
992019
Privacy-preserving machine learning: Methods, challenges and directions
R Xu, N Baracaldo, J Joshi
arXiv preprint arXiv:2108.04417, 2021
932021
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
902019
Detecting Poisoning Attacks on Machine Learning in IoT Environments
N Baracaldo
IEEE International Congress on Internet of Things (ICIOT), 2018
892018
Mitigating Bias in Federated Learning
A Abay, Y Zhou, N Baracaldo, S Rajamoni, E Chuba, H Ludwig
arXiv preprint arXiv:2012.02447, 2020
882020
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
732012
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
712021
Federated Unlearning: How to Efficiently Erase a Client in FL?
A Halimi, S Kadhe, A Rawat, N Baracaldo
arXiv preprint arXiv:2207.05521, 2022
612022
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
562021
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
472019
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
472019
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
472019
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