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Nathalie Baracaldo
Nathalie Baracaldo
IBM Almaden Research Center, 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
4852019
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
4112018
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
2802018
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
1732019
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
1092020
An Adaptive Risk Management and Access Control Framework to Mitigate Insider Threats
N Baracaldo, J Joshi
Computers & Security 39, 237-254, 2013
942013
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
842017
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
672012
Privacy-Preserving Process Mining
F Mannhardt, A Koschmider, N Baracaldo, M Weidlich, J Michael
Business & Information Systems Engineering 61 (5), 595-614, 2019
662019
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
602020
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
542018
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
532019
User-centered and privacy-driven process mining system design for IoT
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
International Conference on Advanced Information Systems Engineering, 194-206, 2019
372019
User-Centered and Privacy-Driven Process Mining System Design for IoT
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
International Conference on Advanced Information Systems Engineering, 194-206, 2019
372019
User-centered and privacy-driven process mining system design for iot
J Michael, A Koschmider, F Mannhardt, N Baracaldo, B Rumpe
International Conference on Advanced Information Systems Engineering, 194-206, 2019
372019
Shared data encryption and confidentiality
E Androulaki, N Baracaldo, JS Glider, A Sorniotti
US Patent 9,397,832, 2016
372016
Reconciling End-to-End Confidentiality and Data Reduction In Cloud Storage
N Baracaldo, E Androulaki, J Glider, A Sorniotti
Proceedings of the 6th edition of the ACM Workshop on Cloud Computing …, 2014
372014
Securing Data Provenance in Internet of Things (IoT) Systems
N Baracaldo, LAD Bathen, RO Ozugha, R Engel, S Tata, H Ludwig
International Conference on Service-Oriented Computing, 92-98, 2016
312016
Mitigating Bias in Federated Learning
A Abay, Y Zhou, N Baracaldo, S Rajamoni, E Chuba, H Ludwig
arXiv preprint arXiv:2012.02447, 2020
282020
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
242021
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